
GITNUXSOFTWARE REVIEW
AI In IndustryTop 10 Best Production Oee Software of 2026
Editorial roundup comparing production oee software options, including how tools fit different manufacturers and the tradeoffs to review.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
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Framework: Features 40% · Ease 30% · Value 30%
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Guidewheel is the best overall for plants that need guided downtime classification and supervisor review to keep OEE data consistent across shifts, while L2L Production is the stronger alternative for enterprise teams wanting reason-code capture tied to machine state changes for review-ready reporting.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Guidewheel
Workflow-guided downtime classification with confirmation and review steps tied to the OEE reporting lifecycle.
Best for: Fits when plants need guided downtime capture and supervisor review to tighten OEE data quality.
Evocon
Editor pickAutomated downtime summaries that attach reason codes to event streams for shift review.
Best for: Fits when plants need reason-coded downtime and OEE reporting driven by machine events.
L2L Production
Editor pickReason-code driven downtime capture ties machine state transitions to structured classification for review-ready OEE.
Best for: Fits when plants need consistent downtime reason capture plus OEE reporting across shifts.
Comparison Table
Guidewheel
SMBFactory operations platform that captures machine data for OEE, downtime, and throughput monitoring.
Workflow-guided downtime classification with confirmation and review steps tied to the OEE reporting lifecycle.
Guidewheel uses a human-guided workflow builder to capture production performance context alongside machine events for OEE reporting. The system focuses on configuring guided data collection, downtime classification, and review loops that reduce missing reason codes.
Guidewheel also provides an integration path for production tracking feeds so OEE metrics can be computed from connected state and count signals rather than only manual entry. Its differentiation is workflow-driven governance around what operators and supervisors confirm before downtime and performance rollups are finalized.
- +Guided downtime reason capture reduces blank or late entries in shift reviews
- +Configurable approval and review loops support consistent OEE logic across lines
- +Integration for production tracking inputs supports state and count based computations
- +Workflow steps make gap handling visible during real-time reporting
- –Deep OEE calculations depend on disciplined event mapping and reason code setup
- –Workflow configuration work can require iterative refinement with plant users
Production supervisors
Review guided downtime reasons per shift
Fewer missing reason codes
Plant performance analysts
Compute OEE from machine signals
More consistent OEE calculations
Show 1 more scenario
Operations governance teams
Enforce operator confirmation steps
Stronger event definition control
Governance roles require specific inputs and review loops for downtime and performance context.
Best for: Fits when plants need guided downtime capture and supervisor review to tighten OEE data quality.
Evocon
SMBProduction monitoring software focused on OEE, downtime analysis, and shift reporting for factories.
Automated downtime summaries that attach reason codes to event streams for shift review.
Evocon fits teams that need end-to-end OEE reporting from shop-floor events rather than spreadsheets and manual rollups. The product focuses on capturing machine state changes and downtime reasons, then mapping them to OEE components for reporting. It also supports operational workflows that require consistent definitions across shifts and assets.
A key tradeoff is that accurate downtime requires disciplined reason coding and stable machine event mapping, which can add setup effort for complex production lines. Evocon works best when connectivity to machines is already planned or can be standardized across similar equipment.
- +Event-driven OEE calculations using machine state changes and reason-coded downtime
- +Shift-ready reporting that keeps definitions consistent across assets
- +Configuration supports loss categorization tied to daily review workflows
- +Dashboards are built around plant decision points, not only KPI charts
- –Requires careful downtime reason coding to prevent misleading OEE outputs
- –Integration setup can be time-consuming for mixed machine protocol environments
Operations managers
Daily OEE review with downtime reasons
Faster shift-level troubleshooting
Manufacturing engineers
Six-loss mapping for loss analysis
Clearer priority for changes
Show 2 more scenarios
Maintenance supervisors
Machine downtime tracking for response
Less unplanned downtime
Supervisors use captured downtime events and reasons to plan corrective actions by asset and pattern.
Plant data owners
Standardized reporting definitions across lines
More trustworthy trend reporting
Data owners enforce consistent categorization so multi-line reporting stays comparable over time.
Best for: Fits when plants need reason-coded downtime and OEE reporting driven by machine events.
L2L Production
enterpriseConnected manufacturing software with OEE, downtime tracking, and plant performance management.
Reason-code driven downtime capture ties machine state transitions to structured classification for review-ready OEE.
L2L Production is built around automated production tracking that converts live equipment and production events into OEE metrics and structured downtime reporting. Operators can use reason-code prompts tied to machine state changes, and supervisors can review the results in dashboards mapped to shift and line context. The integration depth matters most when plants already have industrial connectivity and want fewer manual transfers between historians, SCADA screens, and spreadsheets.
A key tradeoff is that clean downtime logic and reason-code definitions require disciplined setup for each asset. L2L Production fits best when a plant needs consistent downtime classification across shifts and teams instead of one-off analysis per analyst.
- +Automated downtime classification flow with reason-code prompts
- +OEE dashboards that align with shift and line review cadence
- +Integration configuration designed for ongoing plant operations
- +Structured event history supports drill-down during reviews
- –Reason-code governance needs strong plant standardization
- –Some integration work can be asset-specific and time-consuming
- –Dashboard configuration depth can slow initial rollout
- –Advanced reporting depends on correct signal mapping
Manufacturing operations leaders
Shift-level OEE review with downtime breakdown
More repeatable weekly problem solving
Maintenance and reliability teams
Standardized downtime classification for work planning
Faster corrective action targeting
Show 2 more scenarios
Operations analysts
Event drill-down from dashboards
Reduced time spent reconciling data
Analysts trace low OEE periods to underlying event timelines and validate the mapped signals.
Plant system administrators
Integration governance for multiple assets
Fewer manual data handoffs
Administrators manage connector settings and user access so reporting stays consistent across lines.
Best for: Fits when plants need consistent downtime reason capture plus OEE reporting across shifts.
MachineMetrics
SMBManufacturing analytics software that delivers real-time OEE, machine monitoring, and production visibility.
Event-driven production tracking that converts connected machine signals into governed machine states for automated downtime attribution.
MachineMetrics targets plant teams that already have machine connectivity and need OEE calculations without forcing operators to enter every reason code at a terminal. It uses integrations for industrial data collection and maps that into machine state and production context so reporting can update as events arrive. Admin controls center on configuration and governed access for plant and operations roles that need different permissions.
- +Automates downtime capture from machine events to reduce manual reason entry
- +Config-driven integrations map telemetry into consistent OEE reporting outputs
- +Built-in workflows support faster review cycles for shop-floor issues
- +Role-based access supports separating operations and administration duties
- –Requires signal-quality tuning to prevent noisy state transitions
- –Advanced mappings and automation need implementation effort from integration specialists
- –Less effective when production context cannot be aligned to machine events
Plant operations leaders
Shift review of losses and downtime patterns
Fewer manual investigations
Industrial engineering teams
Bottleneck analysis across connected assets
Faster constraint confirmation
Show 2 more scenarios
Maintenance planners
Root-cause follow-up on recurring stops
Lower repeated downtime
Workflows route recurring downtime instances into structured investigation loops tied to machine events.
Quality managers
Yield monitoring tied to machine operation windows
More targeted quality actions
Production tracking aligns quality signals with operating periods to support targeted checks after performance drops.
Best for: Fits when plants need automated OEE reporting from live machine signals and controlled review workflows.
Mingo Smart Factory
SMBManufacturing analytics platform that tracks OEE, downtime, and production efficiency in real time.
Downtime reason capture tied to machine state transitions for loss accounting with consistent operator workflows.
Mingo Smart Factory provides production OEE tracking by combining shop-floor machine signals with downtime reason capture and performance measurement.
- +Automated machine state capture reduces manual downtime logging workload
- +Downtime reason code workflow supports consistent loss categorization
- +Shift-aware OEE calculations align reporting with operational schedules
- +Integration-focused configuration supports faster connectivity to plant systems
- –Reason code setup requires governance to prevent inconsistent loss reporting
- –API and automation surface details are limited compared with OEE leaders
- –Deep MES lineage and traceability depend on external system mapping
- –Advanced analytics for bottleneck decomposition are less explicit than peers
Production supervisors
Review shift-level OEE outcomes
Consistent daily handovers
Operations and quality teams
Link events to production records
Clearer production history
Show 2 more scenarios
Quality managers
Correlate quality with process performance
Better root-cause context
Quality managers review quality results alongside run-level machine or process signals.
Discrete manufacturing operators
Record step outcomes by route
More consistent execution records
Operators follow work-order routes and record outcomes at each bill-of-process step.
Best for: Fits when plant teams need practical OEE reporting from machine states with reason-code discipline.
TEEPTRAK OEE
vertical specialistCloud OEE software that connects machines and tracks availability, performance, and quality.
Reason-code driven downtime capture that feeds OEE availability and loss views with shift-aware context.
TEEPTRAK OEE targets production teams that need OEE reporting grounded in shop-floor signals and reason-code capture. The software focuses on downtime tracking workflows, including categorization and shift-based views used to compute availability, performance, and quality.
- +Downtime reason-code workflow aligns OEE loss events with operator-visible categories
- +Shift-aware reporting supports operations reviews tied to staffing and schedules
- +Event-to-production linkage reduces manual reconciliation between logs and metrics
- +Configuration controls help standardize loss definitions across multiple lines
- –Initial integration can be heavy when data sources use multiple connectivity patterns
- –Advanced analytics require disciplined signal mapping from equipment and quality systems
- –Some OEE configurations depend on careful rule setup to avoid misclassified downtime
- –Live views can feel less granular than tools built around deep historian modeling
Production managers
Track availability by shift
Shift-ready OEE views
Maintenance supervisors
Categorize downtime with reason codes
More usable downtime data
Show 2 more scenarios
Manufacturing engineers
Correlate events to throughput
Less manual spreadsheet work
Teams connect machine integration inputs to link events with real throughput signals.
Plant admins
Standardize event definitions
Consistent event governance
Admins configure downtime and operational setup so teams use consistent event definitions across lines.
Best for: Fits when plant teams need consistent downtime reason-code capture and OEE math tied to real machine events.
Critical Manufacturing MES
enterpriseMES software with real-time production monitoring, traceability, quality, and OEE analysis.
Reason-code driven downtime attribution combined with production-order and work-center rollups for OEE reporting.
Critical Manufacturing MES captures shop-floor events and uses them to drive OEE calculations tied to production orders and work centers. The system connects to equipment via common industrial integration patterns and can generate downtime reason codes from operator inputs and machine state changes.
- +OEE rollups link production activity to orders and work centers for traceable reporting
- +Downtime reason code capture supports both manual entries and inferred machine state changes
- +Integration-oriented connectors fit common MES-to-plant historian and SCADA data paths
- +Shift-based production tracking keeps operational KPIs aligned with staffing plans
- –Meaningful downtime attribution depends on disciplined reason-code configuration by plant teams
- –Onboarding to production workflows requires more configuration than lighter OEE-only tools
Manufacturing operations teams
Monitor machine states with jobs
Clear equipment performance view
Aerospace manufacturers
Maintain serialized production history
Linked history per unit
Show 2 more scenarios
Manufacturing IT teams
Align orders with shop-floor events
Shared execution record
IT teams coordinate order context with shop-floor events across connected production systems.
Production supervisors
Track work across multi-step routes
Better WIP visibility
Supervisors move work orders through routes while showing live job status and operational progress.
Best for: Fits when plant teams need order-tied OEE and downtime reason code capture across shifts.
Tulip OEE
API-firstComposable manufacturing software for building OEE, downtime, quality, and production applications.
Downtime reason collection and follow-on actions are implemented as line workflows inside Tulip app logic.
Tulip OEE is a production OEE app and analytics workflow built on Tulip’s visual app builder. It collects machine and operator signals, lets teams define downtime reason capture on the line, and computes availability, performance, and quality metrics in the same production context.
- +Visual app workflows connect operator input to OEE calculations in one place
- +Downtime reason capture can be enforced at the point of event reporting
- +Configurable screens support shift handoffs with consistent production records
- +Integration options enable mapping machine signals into plant reporting
- –OEE accuracy depends on disciplined downtime reason coding by operators
- –Deeper commissioning work is needed for reliable machine connectivity
Operations managers
Run line OEE with downtime capture
More accurate OEE tracking
Maintenance supervisors
Turn OEE events into work tasks
Faster corrective action cycles
Show 2 more scenarios
Plant data engineers
Integrate signals and export OEE context
Consistent enterprise reporting
Brings shop-floor data into Tulip and sends OEE results back to plant systems.
Production operators
Capture operator downtime reasons at line
Better loss attribution
Provides operator-facing tasks to record stoppages in the production context.
Best for: Fits when plants want operator-guided OEE data capture and workflow automation around events.
Autodesk Fusion Operations
SMBCloud manufacturing execution software for production tracking, quality, labor, and equipment performance.
Fusion Operations ties OEE reporting to Autodesk manufacturing records for continuity from planned work to shop-floor tracking.
Autodesk Fusion Operations centers OEE production tracking on the Autodesk ecosystem, tying factory reporting workflows to Fusion-based manufacturing data. It focuses on shift-level production visibility with connected device inputs and event-driven downtime capture to support availability, performance, and quality views.
- +Integration paths align with Autodesk workflows and downstream manufacturing records
- +Event-driven downtime capture supports faster reason-code adoption
- +Works well when machine connectivity already feeds manufacturing context
- +Provides configuration options for production tracking across shifts
- –OEE deployment depends on solid connectivity and event mapping design
- –Advanced analytics often require additional integration work
- –Reason-code workflows need careful plant governance to stay consistent
- –Reporting templates can feel restrictive for highly custom shop-floor models
Manufacturing engineering teams
OEE tracking from Fusion process data
Faster downtime attribution
Plant operations supervisors
Shift handover visibility with web dashboards
More consistent shift decisions
Show 2 more scenarios
Production data analysts
Event-driven downtime capture workflows
Cleaner OEE datasets
Analysts standardize downtime categories using event feeds from production-connected devices.
Operations technology teams
Autodesk ecosystem integration for reporting
Reduced integration effort
OT teams connect plant reporting workflows to Autodesk manufacturing data without rebuilding an OEE-only stack.
Best for: Fits when plants need OEE reporting tied to Autodesk manufacturing data and controlled device event mapping.
Oden Technologies
emergingIndustrial analytics platform that supports OEE improvement through production data, monitoring, and AI analysis.
Automated OEE timeline that binds machine state, downtime reasons, and production tracking in one event sequence.
Oden Technologies targets plant teams that need OEE reporting tied to machine state changes instead of spreadsheet rollups. It centers on automated production tracking with downtime reason capture and links performance and quality signals to the same event timeline.
- +Event-driven downtime reason capture aligned with machine state transitions
- +Integration-focused design for PLC and industrial data sources
- +Automated production tracking reduces operator time on manual logkeeping
- +Configurable reporting views for shift-level and production-period OEE analysis
- –Requires careful mapping of downtime codes to controller signals
- –Advanced analytics depends on maintaining clean event timestamps across sources
Manufacturing engineering teams
OEE by machine state change events
Faster OEE reporting cycles
Operations managers
Event timeline performance and quality links
Improved shift decision-making
Show 2 more scenarios
Plant IT and integration staff
Controller data flows into OEE analytics
Reduced integration effort
Supports industrial connectivity patterns to route controller and related signals into reporting.
Continuous improvement teams
Downtime reason capture tied to events
More actionable improvement actions
Standardizes loss coding on the exact machine events that caused downtime and throughput loss.
Best for: Fits when plant teams need event-driven OEE with automated downtime reason capture and controller-based connectivity.
Conclusion
After evaluating 10 production oee software, Guidewheel stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Production Oee Software
Production OEE software turns machine state changes and operator or event inputs into availability, performance, and quality metrics that teams can review per shift and per line. This buyer guide covers L2L Production, MachineMetrics, Evocon, Guidewheel, Mingo Smart Factory, Oden Technologies, Autodesk Fusion Operations, TEEPTRAK OEE, Critical Manufacturing MES, and Tulip OEE.
Across these tools, the main differentiators show up in how downtime reason codes are captured and governed, how events are mapped into OEE calculations, and how much workflow structure exists for shift review and approvals. Plant teams should focus on integration depth to PLC and production systems and on automation and API surfaces that keep event timestamps and machine states consistent.
Production OEE Software that calculates availability, performance, and quality from governed events and downtime reason codes
Production OEE software calculates OEE by tying machine state transitions and production signals to structured downtime reason codes and loss events for availability, performance, and quality reporting. L2L Production emphasizes reason-code driven downtime capture that classifies machine state transitions into structured categories for review-ready OEE.
Some platforms center on event-driven production tracking that converts connected machine signals into governed machine states for automated downtime attribution, which is the core approach in MachineMetrics. Others add workflow-guided capture and confirmation loops, like Guidewheel, to reduce blank or late downtime reason entries during shift review.
Downtime reason capture, event-to-OEE mapping, and shift governance controls
Production OEE software relies on a clean chain from machine state transitions to structured downtime reason codes so availability and loss reporting stay reviewable. L2L Production leads with reason-code driven downtime capture that ties machine state transitions to structured classification for review-ready OEE.
Reason-code capture workflows tied to machine state changes
L2L Production ties downtime reason capture to machine state transitions with structured classification prompts. Guidewheel and Mingo Smart Factory add reason-code workflows that guide operators through capture and loss categorization to support shift review cadence.
Event-driven OEE calculations from governed production signals
MachineMetrics converts connected machine signals into governed machine states to automate downtime attribution and OEE reporting outputs. Evocon and Oden Technologies compute OEE from event streams by attaching reason codes to state change sequences for shift-ready summaries.
Shift review and approval loops for downtime completeness
Guidewheel includes configurable approval and review loops that connect guided downtime classification steps to the OEE reporting lifecycle. Tulip OEE implements downtime reason collection and follow-on actions as line workflows inside Tulip app logic to enforce structured input at the point of event reporting.
Order-tied rollups for traceable reporting across work centers
Critical Manufacturing MES combines reason-code driven downtime attribution with production-order and work-center rollups for OEE reporting across shifts. Mingo Smart Factory emphasizes consistent operator workflows for practical OEE reporting driven by machine states and reason discipline.
Integration orientation toward industrial connectivity and production systems
Oden Technologies centers on integration-focused design for PLC and industrial data sources while binding machine state, downtime reasons, and production tracking into one event sequence. Autodesk Fusion Operations ties OEE reporting to Autodesk manufacturing records for continuity from planned work to shop-floor tracking.
Choose by integration depth and by how downtime reason governance is enforced
Plants should map the real loss capture workflow first because OEE math accuracy depends on whether downtime reasons are prompted, validated, and reviewed consistently. L2L Production and MachineMetrics emphasize automated downtime capture driven by machine state changes to reduce manual reason entry.
Pick the downtime capture philosophy that matches the plant’s current discipline
If downtime reasons must be classified consistently with prompts and structured review readiness, L2L Production fits the machine-state-to-reason capture pattern with automated classification flow. If downtime reasons must be derived from event streams using machine state changes and reason-coded downtime, Evocon offers shift-ready reporting that keeps definitions consistent across assets.
Decide whether to rely on automated state transitions or guided operator confirmation
MachineMetrics and Oden Technologies automate downtime attribution by converting connected machine signals into governed machine states and then binding reasons to the OEE timeline. Guidewheel reduces missing or late reason entries by attaching confirmation and review steps to the OEE reporting lifecycle.
Validate the event mapping effort against the equipment and data sources mix
If the plant has varied machine protocol environments, integration setup can become time-consuming for event mapping, which is explicitly called out for Evocon. If signal-quality tuning is feasible and integration specialists can implement advanced mappings, MachineMetrics can convert live telemetry into controlled machine states.
Align reporting rollups to how production work is actually managed
If OEE reporting must tie downtime attribution to production-order and work-center structures, Critical Manufacturing MES provides order-tied rollups for traceable reporting. If reporting needs are primarily line and shift cadence, L2L Production aligns dashboards with shift and line review cadence tied to reason-code governance.
Set expectations for connectivity commissioning effort based on controller dependencies
Oden Technologies depends on careful mapping of downtime codes to controller signals and on maintaining clean event timestamps across sources to keep advanced analytics reliable. Tulip OEE provides line workflow logic for capture, but deeper commissioning work is needed for reliable machine connectivity to keep OEE accuracy stable.
Plant teams that need governed OEE from events, reasons, and shift workflows
Manufacturing teams that cannot tolerate inconsistent downtime reasons benefit from platforms that tie downtime classification to structured workflows and machine state changes. L2L Production and MachineMetrics prioritize automation that converts events into governed machine states for automated downtime attribution and shift reporting.
Plants standardizing downtime reason governance across shifts
L2L Production uses reason-code prompts and structured classification tied to machine state transitions to keep definitions consistent across shift and line review cadence.
Operations teams pushing for automated downtime attribution from connected telemetry
MachineMetrics builds governed machine states from machine signals and uses config-driven integrations to map telemetry into consistent OEE reporting outputs.
Supervisors who need approval loops to reduce incomplete downtime capture
Guidewheel ties guided downtime classification with confirmation and configurable approval and review loops to the OEE reporting lifecycle.
Production planners who need OEE rollups tied to orders and work centers
Critical Manufacturing MES links reason-code downtime attribution to production-order and work-center rollups so OEE reporting stays traceable.
Companies using Autodesk manufacturing records as the source of planned work
Autodesk Fusion Operations aligns OEE reporting with Autodesk workflows so event-driven downtime capture supports continuity from planned work to shop-floor tracking.
Common procurement and rollout mistakes in Production OEE Software
Many rollout failures come from treating downtime reason entry as an optional step instead of a governance-controlled workflow. Reason-code governance discipline is repeatedly called out as a dependency for products that classify or infer downtime from machine events.
Installing an event-driven OEE tool without a plant-wide downtime reason coding standard
L2L Production warns that reason-code governance needs strong plant standardization. Evocon also flags careful downtime reason coding to prevent misleading OEE outputs.
Assuming machine signals will produce clean state transitions without tuning or mapping work
MachineMetrics requires signal-quality tuning to prevent noisy state transitions. Oden Technologies requires careful mapping of downtime codes to controller signals and clean event timestamps across sources.
Configuring workflows without allocating time for iterative refinement with plant users
Guidewheel notes that workflow configuration can require iterative refinement with plant users. Tulip OEE notes that deeper commissioning work is needed for reliable machine connectivity even with line workflow capture logic.
Over-indexing on OEE dashboards without aligning rollups to how work is tracked
Critical Manufacturing MES explicitly connects downtime attribution with production-order and work-center rollups, so skipping that alignment breaks traceable reporting. L2L Production instead aligns OEE dashboards with shift and line review cadence, so order-level expectations need an explicit plan.
How We Selected and Ranked These Tools
We evaluated each production OEE software on automation and event-to-OEE mapping coverage, then weighed how reliably downtime reason capture turns machine state transitions into structured loss classification. Features accounted for 40% of the scoring because reason-code driven capture patterns differ sharply between L2L Production, MachineMetrics, and Guidewheel.
Ease of use and overall value each accounted for 30% because integrations and workflow configuration effort can dominate rollout timelines for event-mapping-heavy platforms like Evocon and Oden Technologies. L2L Production earned the top ranking for its reason-code driven downtime capture that ties machine state transitions to structured classification for review-ready OEE across shift and line review cadence.
Frequently Asked Questions About Production Oee Software
How do L2L Production and MachineMetrics handle downtime reason codes from machine state changes?
Which tool is better when OEE math must be tied to production orders and work centers rather than line-level events?
How do Guidewheel and Tulip OEE reduce missing downtime reasons during shift review?
When does an administrator need RBAC and audit logs in production OEE software?
What breaks if downtime classification stays in a spreadsheet while Evocon expects event-driven reason-coded summaries?
How do Mingo Smart Factory and Oden Technologies connect production tracking to machine runtime state?
How does data migration typically work when replacing an existing OEE workbook or historian workflow with TEEPTRAK OEE?
What integration approach changes the most between Autodesk Fusion Operations and a plant-first connector model like TEEPTRAK OEE?
When should a plant choose Guidewheel over MachineMetrics for governance around what gets finalized?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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