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Top 10 Best Chinos AI on Model Photography Generator of 2026
Compare chinos ai on model photography generator tools and use cases for model photo creation, with options like RAWSHOT AI and Vmake.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
Agents extract product evidence with provenance, then collect written reviews and transcribe video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
RAWSHOT AI is the best pick for e-commerce managers, designers, and brand teams launching chinos because it turns your existing product photos into original fashion imagery with seven editable stages, so you can fine-tune model, lighting, and composition without breaking the rest of the look, while Vmake is a strong alternative for sellers who need on-model photos from garment images without booking a studio, thanks to its combined model generation, background removal, and enhancement workflow.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
RAWSHOT AI
RAWSHOT AI exposes the shoot as seven editable stages, from product and model through lighting and composition. Users select the options directly, and changing one element leaves the other composition choices in place; they can also begin with an Inspiration Gallery look and edit its settings.
Best for: E-commerce managers, designers and brand teams preparing chinos launches who need original product imagery for product pages, lookbooks, marketing campaigns or social content.
Vmake
Editor pickVmake combines its AI Fashion Model generator with background removal and image enhancement in one editing workflow.
Best for: Fits when apparel sellers need model photos from existing chinos product images without arranging a studio shoot.
Pebblely
Editor pickAI Fashion Model generation turns uploaded clothing photos into model-worn images without a photographed model.
Best for: Fits when lean ecommerce teams need quick apparel campaign variants from existing garment photos.
Comparison Table
RAWSHOT AI
Fashion photoshoot generation softwareRAWSHOT AI turns chinos product photos, flat-lays, mockups or technical sketches into original fashion images with selectable models, styling, backgrounds, lighting and camera direction.
RAWSHOT AI exposes the shoot as seven editable stages, from product and model through lighting and composition. Users select the options directly, and changing one element leaves the other composition choices in place; they can also begin with an Inspiration Gallery look and edit its settings.
RAWSHOT AI is a browser-based virtual photo studio for clothing, footwear, jewellery, bags, watches, eyewear and accessories. For chinos, users can select a model, pose, styling, light, background, camera view and frame, then generate original imagery from their product assets. The discrete controls make it possible to change one choice while keeping the rest of that composition in place.
An e-commerce team preparing a chinos launch can configure images for several colourways within one photoshoot and keep the chosen composition consistent. The tradeoff is that RAWSHOT AI offers one accuracy-first image style; teams seeking a graded or highly stylized look will need to finish that work in another tool.
- +Full and permanent commercial rights to every generation, with no ongoing licensing fees on library models.
- +1,200+ licence-free adult models, plus a private model builder.
- +Five tokens an image. That's the whole pricing model.
- +15 image frames across four groups, from full body down to hand-and-wrist, ankle, ear and eye detail.
- –Brands needing a specific real model or ambassador must use a workflow built around that person.
- –Teams seeking graded or highly stylized imagery need another tool, since RAWSHOT AI ships one image style.
E-commerce managers
Chinos product-page imagery
Original product-page visuals
Independent fashion designers
Pre-launch collection imagery
Launch-ready collection visuals
Show 1 more scenario
Social content managers
Chinos campaign assets
Still and video content
Turn finished chinos images into short videos and select the scenes, camera motions and model actions.
Best for: E-commerce managers, designers and brand teams preparing chinos launches who need original product imagery for product pages, lookbooks, marketing campaigns or social content.
Vmake
SMBAI product photography platform with on-model fashion image generation capabilities.
Vmake combines its AI Fashion Model generator with background removal and image enhancement in one editing workflow.
Vmake suits apparel sellers who have flat-lay or mannequin images but need model photos for product listings. Model and scene choices provide alternate looks, while adjacent editing tools handle background cleanup and image enhancement.
Generated results can change small garment details, so chinos images need a product review before publication. The workflow supports image creation and editing, not verified fit measurements or physical garment simulation.
- +Creates model-worn apparel images from garment product photos.
- +Model and scene choices offer alternate catalog treatments.
- +Background removal and image enhancement sit alongside model generation.
- –Generated waistbands, pockets, and stitching can differ from the source garment.
- –Chinos colors and leg shapes need manual review before listing.
- –The image workflow does not provide verified fit measurements.
Small apparel brands
Creating chinos listing images
More listing imagery
Ecommerce catalog teams
Refreshing mannequin photography
Updated product visuals
Show 1 more scenario
Independent clothing sellers
Preparing campaign variants
Alternate campaign images
Selectable models and scenes provide alternate presentations of chinos without a new photo session.
Best for: Fits when apparel sellers need model photos from existing chinos product images without arranging a studio shoot.
Pebblely
SMBAI product image generation tool that creates fashion and ecommerce visuals from uploaded photos.
AI Fashion Model generation turns uploaded clothing photos into model-worn images without a photographed model.
Pebblely generates model-worn apparel images by using uploaded clothing photos and producing on-model fashion visuals for campaign and catalog usage. Users can select an AI model and generate scenes with chosen or described backgrounds, then iterate on alternate visuals without arranging a physical shoot. The tool prioritizes image creation over technically preserving garment construction, so logos, print details, and fit presentation can shift and require review before use.
For chinos AI on model photography generator workflows, Pebblely fits teams that need faster on-model coverage when original shoot schedules cannot support every angle or scene. A common tradeoff is that generated garment attributes can deviate from the source photo, so quality checks against the original reference are needed. It works best when the goal is creating reusable on-model imagery for product pages and marketing drafts rather than guaranteeing pixel-accurate construction.
- +Prompted backgrounds and preset scenes create alternate campaign looks from a single source image.
- +Product-photo generation also covers non-apparel catalog assets, supporting mixed-category storefronts.
- +Browser workflow avoids requiring a studio setup or dedicated image-editing software.
- –Logos, prints, and small construction details can change between outputs.
- –No controls for exact garment fit, seam placement, or pose mapping limit product-accuracy workflows.
- –Browser-first creation has no documented API or direct catalog sync for automated publishing.
Fashion brands and merchandising teams
Create chinos on-model pose variations
Reusable on-model visuals
E-commerce teams and online retailers
Refresh chinos catalog without reshoots
Broader image coverage
Show 2 more scenarios
Fashion marketers and creative teams
Produce coordinated chinos lookbook sets
Lookbook-ready imagery
Generate a consistent set of model-led visuals to support editorial lookbooks and campaign layouts.
Catalog and product operations teams
Fill missing chinos angles
More complete sets
Create extra on-model views and scene variations to cover gaps in existing product photography.
Best for: Fits when lean ecommerce teams need quick apparel campaign variants from existing garment photos.
VModel
SMBAI fashion model photography generator for e-commerce clothing stores.
Pairs selectable AI model looks with garment-image generation in a single browser workflow.
Small ecommerce teams can upload a garment image, choose an AI model look, and create product visuals in a browser workflow. Model and scene options help produce different creative treatments from the same source garment without coordinating a shoot.
- +Turns uploaded apparel images into model-worn product visuals without booking a studio shoot.
- +Model appearance and scene choices support varied campaign concepts from the same garment.
- +Browser-based image creation suits lean ecommerce teams without dedicated photo studios.
- –Generated logos, prints, and seam details can diverge from the source garment.
- –Images do not verify physical fit, sizing, or fabric behavior.
- –Teams still need manual image review and SKU-level catalog organization.
Small apparel retailers
Creating listing images
More listing visuals
Fashion marketing teams
Testing campaign concepts
Faster creative review
Show 1 more scenario
Online clothing brands
Refreshing product imagery
Additional image variants
Brands can produce alternate product visuals from existing garment photos for selected listings.
Best for: Fits when apparel sellers need varied product imagery without coordinating a physical model shoot.
PhotoRoom
SMBAI photo editing platform with product image generation, background replacement, and ecommerce content tools.
AI Fashion Models generates model-worn apparel images inside the editor used for background removal, scene creation, and product-image finishing.
PhotoRoom suits apparel sellers who need model-led catalog images without arranging a physical shoot, combining garment generation with its product-photo editor. Users upload apparel, select an AI model and scene, then refine the result with background removal, AI backgrounds, and resizing.
- +Model and scene selection turns uploaded apparel into catalog-ready lifestyle images.
- +Background removal, AI backgrounds, and resizing are available in the same editor.
- +Image-editing API endpoints support connected product-image workflows.
- –Generated prints, seams, and logos can differ from the source garment.
- –Fit and fabric behavior have less dedicated control than in apparel visualization software.
- –The API documentation centers on image editing rather than fashion-model generation.
Fashion sellers and apparel brands
Compose chinos on-model apparel visuals
Model-led options
Online sellers and marketplace operators
Generate listing images for chinos
More consistent listings
Show 2 more scenarios
Jewelry sellers and independent retailers
Create clean cutouts with styled scenes
Catalog images without studios
Generate styled scenes from product images and review generated details for catalog-ready cutouts.
Small brands and product marketers
Place chinos into generated environments
Lifestyle variants
Create lifestyle variants by placing products into AI backgrounds for marketing images.
Best for: Fits when apparel teams need quick model-led catalog images and can manually inspect each generated garment.
Vue.ai
enterpriseAI-powered product photography and on-model styling platform for fashion retailers.
VueModel creates AI fashion-model images from existing garment product photos, with synthetic model and pose variations.
In apparel catalog production, Vue.ai pairs AI-generated model photography with a wider retail automation suite. Its VueModel workflow turns existing garment product images into synthetic model photos with variations in models, poses, and backgrounds. Catalog tagging and other retail tools extend the workflow beyond image generation, though teams focused only on chinos photography may not need the wider suite.
- +Generates model photos from existing garment product images.
- +Model and pose variations support catalog updates without new physical shoots.
- +Catalog tagging tools connect image production with broader product-content workflows.
- –Pose changes can affect garment details, so chinos images need review before publication.
- –API-level generation controls and catalog-system integration are not clearly detailed in product materials.
- –The wider retail suite may add evaluation work for teams seeking image generation alone.
Apparel product and merchandising teams
Preview chinos on selected model poses
Faster garment evaluation
Accessory merchandising teams
Generate on-model belt views with chinos
More consistent views
Show 2 more scenarios
Fashion marketing teams
Build lifestyle chinos fashion scenes
More campaign visuals
Combine garments, model direction, backgrounds, and styling for lifestyle-oriented product imagery.
Ecommerce catalog teams
Standardize chinos on-model listing images
Uniform product visuals
Create consistent on-model visuals for apparel listings from existing garment product inputs.
Best for: Fits when apparel teams need synthetic model imagery from catalog photos and can review outputs before publication.
Caspa
SMBAI ecommerce image generator that creates product photos, lifestyle scenes, and edited catalog visuals.
Generates synthetic model scenes around uploaded product photography, combining people and settings in one image workflow.
Caspa generates model-led product images from uploaded product photos, giving fashion sellers an alternative to arranging a live shoot. Users can combine synthetic models with generated backgrounds to create ecommerce and social campaign imagery.
- +Creates model-led scenes from existing product photos.
- +Combines synthetic models and generated backgrounds in one image workflow.
- +Produces campaign imagery without arranging a physical model shoot.
- –Generated seams, prints, and garment proportions can differ from the source item.
- –No API or catalog-system integration supports automated publishing.
- –Consistent model and pose selection across large SKU sets can require repeated generation.
Apparel sellers and ecommerce merchandising teams
Convert chinos photos into model listings
More listing visuals
Online retailers and brand marketers
Create chinos lifestyle scenes
Lifestyle imagery for storefronts
Show 2 more scenarios
Fashion creatives and freelance designers
Prototype chinos styling and poses
Quick visual prototypes
Explore pose and wardrobe variations with editorial crops for quick concept and mockup development.
Fashion brands and catalog teams
Update chinos catalog and lookbooks
More consistent assets
Generate coordinated model shots across collection styling variations for broader catalog coverage.
Best for: Fits when fashion sellers need model imagery from product photos without arranging a live shoot.
Veesual
enterpriseVirtual try-on and model visualization software for fashion ecommerce imagery.
Veesual Mix & Match lets shoppers compose outfits from catalog items within the retail browsing flow.
Veesual brings shopper-facing virtual try-on and outfit composition to apparel ecommerce rather than focusing on standalone image production. Fashion Try-On lets shoppers view garments on models, while Mix & Match combines catalog pieces into complete looks. This supports product discovery, but the workflow is a less direct fit for teams producing repeatable chinos catalog photography or large sets of finished assets.
- +Fashion Try-On puts garment visualization inside the shopper journey.
- +Mix & Match lets shoppers combine separate catalog pieces into complete looks.
- –The core experience serves shoppers, not production teams exporting finished chinos imagery.
- –Production teams get limited emphasis on repeatable pose, backdrop, and lighting controls.
Fashion ecommerce catalog teams
Batch-generate chinos on-model images
Repeatable product visuals
Apparel product teams
Create multi-angle chinos coverage
Broader product-page coverage
Show 2 more scenarios
Fashion retailers
Visualize chinos on generated models
Model-worn shopper views
Present chinos on generated or selected models for interactive fashion visualization.
Fashion creative teams
Previsualize chinos for lookbooks
Draft campaign concepts
Explore models, poses, and coordinated garments before committing to campaign production.
Best for: Fits when retailers want shoppers to visualize chinos with catalog pieces, not generate studio-ready image libraries.
OnModel
SMBAI tool that turns flat lays and mannequin shots into model photos for ecommerce listings.
Model appearance selection lets sellers generate alternate human presentations from one uploaded garment image.
OnModel suits apparel sellers who need model photos from existing garment images rather than a new studio shoot. It converts flat-lay and mannequin product shots into model imagery, with selectable model appearance options for creating alternate presentations.
- +Creates model imagery from existing garment photos without arranging a physical shoot.
- +Model appearance options support alternate presentations from the same product image.
- +Image generation gives small apparel catalogs more listing visuals per garment.
- –Generated chinos can shift waistband construction, pocket edges, or leg taper.
- –The core workflow lacks a prominent documented API or PIM integration path.
- –Generated fit and fabric appearance may not support precise product-fit claims.
Merchandisers and fashion marketers
Test chinos model and pose options
Faster imagery evaluation
Apparel retailers and ecommerce teams
Make chinos model-worn listing images
More varied listings
Show 2 more scenarios
Fashion brands and online retailers
Replace mannequin photos for chinos
More human-centered views
Replace mannequin-only presentation with AI-generated human model imagery based on the existing garment source.
Apparel catalog teams
Generate multi-angle chinos views
More complete coverage
Produce alternate angles for chinos using consistent garment coverage from existing product inputs.
Best for: Fits when apparel sellers need model images from existing chinos photos and can review garment details before publishing.
Flair
SMBAI design tool for branded product photos and marketing visuals built for commerce teams.
A layered canvas lets users compose product cutouts, generated fashion models, props, and backgrounds together.
Flair brings product photography into a layered AI canvas, where teams can combine apparel images with generated models, props, and backgrounds rather than relying on a single prompt. Its fashion workflow supports model-led scenes and prompt-based changes to setting and composition for chinos campaigns and social content. Generated images can alter pocket placement, waistband shape, color, or fabric texture, so product details need review before publication.
- +Layered canvas combines product images, generated models, props, and backgrounds in one scene.
- +Prompt-based scene edits support campaign variations without rebuilding every composition.
- +Model-led apparel imagery suits lookbooks and social campaigns built from product photos.
- –Generated chinos can shift pocket placement, waistband shape, or fabric texture.
- –Scene composition and garment corrections require repeated manual image and prompt adjustments.
- –The creator workflow offers limited control for automated generation across large SKU catalogs.
Apparel sellers and fashion marketers
Create model-led chinos campaign scenes
Campaign visuals without shoots
Brand and marketing teams
Generate chinos lifestyle variations
Campaign-ready concepts
Show 2 more scenarios
Ecommerce and merchandising teams
Produce chinos catalog images
More catalog visuals
Generate studio-style chinos product images and background variations from existing product photos.
Catalog and content production teams
Generate repeatable chinos SKU variants
Broader visual coverage
Create image variants across collections, angles, backgrounds, and campaign treatments for broad coverage.
Best for: Fits when apparel teams need model imagery for campaigns and can review garment details before publishing.
How to Choose the Right Chinos AI on Model Photography Generator
This guide covers RAWSHOT AI, VModel, Vmake, Vue.ai, Pebblely, PhotoRoom, Caspa, Flair, Veesual, and OnModel. RAWSHOT AI separates product, model, lighting, and composition into seven editable stages, while VModel generates model-worn visuals from uploaded apparel images.
Vmake combines model generation with background removal and image enhancement, and Flair uses a layered canvas for arranging product cutouts, models, props, and backgrounds. Chinos waistband, pocket, seam, and leg-shape changes require review in tools such as Vmake, PhotoRoom, Flair, and OnModel.
What a Chinos AI On-Model Photography Generator Produces
A chinos AI on-model photography generator creates model-worn apparel images from garment photos or from selected product and model settings. These images support catalog and campaign workflows, but generated apparel visuals do not establish physical fit, sizing, or fabric behavior.
VModel turns uploaded apparel images into model-worn product visuals and offers model appearance and scene choices. RAWSHOT AI lets users edit product, model, lighting, and composition stages independently, while preserving the other composition choices when one element changes.
Chinos Image Generation and Editing Criteria
Chinos images need garment details such as waistbands, pockets, stitching, and leg shape to remain consistent with the source. VModel flags possible changes to logos, prints, and seams, while Vmake calls for review of waistbands, pockets, stitching, color, and leg shape.
The tools differ in how they create and edit images. RAWSHOT AI separates seven settings into editable stages, while Flair uses a layered canvas and Vmake combines model generation with image enhancement.
Garment detail preservation
VModel warns that logos, prints, and seam details can diverge from the source garment. Vmake identifies waistbands, pockets, stitching, chinos color, and leg shape as details that need manual review.
Control over image composition
RAWSHOT AI divides a shoot into seven editable stages and preserves other composition choices when one setting changes. Flair instead arranges product cutouts, models, props, and backgrounds on a layered canvas.
Editing tools in the same workflow
Vmake combines its AI Fashion Model generator with background removal and image enhancement. PhotoRoom places AI Fashion Models alongside background removal, AI backgrounds, and resizing.
Campaign scene variation
Pebblely uses prompted backgrounds and preset scenes to create campaign variations from an uploaded clothing photo. OnModel focuses on choosing alternate model appearances from one garment image.
Retailer or production-team workflow
Veesual places Fashion Try-On and Mix & Match in the shopper journey, where customers combine catalog pieces into outfits. Caspa generates model scenes around uploaded product photography, but does not offer API or catalog-system integration for automated publishing.
Choose by Source Image, Editing Model, and Publishing Workflow
Start by deciding whether the chinos imagery should come from newly selected product and model settings or from an existing garment photo. RAWSHOT AI supports the first approach, while VModel, Vmake, PhotoRoom, and other tools turn uploaded apparel images into model-worn visuals.
Then choose between direct stage controls, a layered composition canvas, or a shopper-facing try-on experience. Those approaches serve different production needs, and generated images still require checks for garment details and physical accuracy.
Choose original image setup or garment-photo transfer
Choose RAWSHOT AI if the team wants to select product, model, lighting, and composition settings across seven stages. Choose VModel or Vmake if the workflow starts with an existing chinos product photo that needs to become a model-worn image.
Pick stage controls or a layered composition
RAWSHOT AI keeps other composition choices in place when one stage changes, which suits teams that want to adjust specific shoot settings. Flair suits teams that prefer to arrange product cutouts, models, props, and backgrounds together, with repeated manual adjustments for scene and garment corrections.
Separate production imagery from shopper try-on
Choose Veesual when the intended experience lets shoppers use Fashion Try-On or Mix & Match while browsing catalog pieces. Choose PhotoRoom or Pebblely for teams producing images from apparel photos rather than building an outfit-composition experience for shoppers.
Decide how much image finishing belongs in the same editor
Vmake combines model generation with background removal and image enhancement. PhotoRoom adds background removal, AI backgrounds, and resizing, while Pebblely offers prompted backgrounds and preset scenes for alternate campaign looks.
Match publishing needs to documented workflow controls
Caspa lacks API or catalog-system integration for automated publishing, and Vue.ai does not clearly detail API-level generation controls or catalog integration. Teams that depend on automated catalog publishing should distinguish these documented limits from image-generation features.
Teams That Benefit from Chinos Model Imagery
E-commerce and brand teams can use these tools to produce model-worn images from garment photos or to configure a new image from product and model settings. RAWSHOT AI also grants full and permanent commercial rights to every generation and provides more than 1,200 licence-free adult models plus a private model builder.
The strongest workflow depends on the intended output. Veesual serves shoppers composing outfits, while tools such as Vmake and PhotoRoom focus on image creation and finishing for apparel teams.
Brand teams creating original chinos campaigns
RAWSHOT AI lets teams edit product, model, lighting, and composition settings across seven stages. Its model library includes more than 1,200 licence-free adult models, and every generation includes full and permanent commercial rights.
E-commerce teams converting existing garment photos
VModel, Vmake, PhotoRoom, and OnModel generate model imagery from uploaded apparel or garment photos. These teams should inspect generated waistbands, seams, logos, pockets, and leg shape before listing.
Lean teams producing campaign alternatives
Pebblely creates prompted-background and preset-scene variations from one clothing photo. Flair lets teams combine cutouts, models, props, and backgrounds on a layered canvas.
Retailers adding outfit visualization to shopping
Veesual's Fashion Try-On and Mix & Match let shoppers visualize chinos with other catalog pieces. Its core experience serves the shopper journey rather than production teams exporting finished image libraries.
Common Chinos Image Workflow Errors
A generated model image can change garment details even when the source photo is accurate. VModel, Vmake, PhotoRoom, Flair, and OnModel all identify specific risks involving prints, seams, waistbands, pockets, or leg shape.
A second error is choosing a tool for the wrong workflow. Veesual focuses on shopper outfit composition, while Caspa does not provide API or catalog-system integration for automated publishing.
Treating a generated chinos image as proof of fit or fabric behavior
VModel states that its images do not verify physical fit, sizing, or fabric behavior. Review the physical garment and product specifications separately from generated visuals.
Approving an image without checking construction details
Inspect waistband construction, pocket edges, seams, logos, prints, color, and leg shape in outputs from Vmake, PhotoRoom, Flair, and OnModel. Flair specifically warns that pocket placement, waistband shape, or fabric texture can shift.
Selecting a shopper try-on product for image-library production
Veesual's Fashion Try-On and Mix & Match serve shoppers composing outfits from catalog items. Its production workflow has limited emphasis on repeatable pose, backdrop, and lighting controls.
Assuming catalog publishing can be automated from every image tool
Caspa does not offer API or catalog-system integration for automated publishing. Vue.ai does not clearly detail API-level generation controls or catalog integration.
How We Selected and Ranked These Tools
We evaluated features at 40% of each score, with ease of use and value weighted at 30% each. We compared the tools' image-generation workflows, editing controls, stated garment-detail limitations, and fit for catalog, campaign, or shopper-facing use.
RAWSHOT AI ranked first with an overall score of 9.0 And feature score of 9.1. Its seven editable shoot stages, commercial rights for every generation, and library of more than 1,200 licence-free adult models set it apart.
Frequently Asked Questions About Chinos AI on Model Photography Generator
Which tools create original chinos imagery, and which work from existing garment photos?
How should teams check that generated chinos still match the real garment?
When is Veesual a better choice than a chinos photography generator?
Can these tools connect chinos image generation to API, PIM, or DAM workflows?
How can teams reuse flat-lay or mannequin images instead of arranging a new shoot?
What image formats or output sizes do these tools provide for chinos campaigns?
What security controls, such as SSO or RBAC, are specified for these tools?
What tradeoff comes with Flair's layered canvas compared with RAWSHOT AI's guided workflow?
How can a team run a focused first test across chinos generators?
Conclusion
After evaluating 10 chinos ai on model photography generator, RAWSHOT AI 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.
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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