Submission Preflight (cogpsych-submission)
SkillAI & modelsUse when running the final pre-submission preflight for Cognitive Psychology (Elsevier) via Editorial Manager, scope/length fit, abstract and keywords, APA-style reporting, model-comparison completeness, reproducible model/analysis code, and the Elsevier research-data and competing-interest declarations. Final checks; it does not draft content. Verify volatile specifics on the official guide for authors.
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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Then ask your AI: use the Submission Preflight (cogpsych-submission) skill
What this skill tells your AI
The instructions your AI receives, as published by brycewang-stanford/awesome-journal-skills in Cognitive-Psychology-Skills/skills/cogpsych-submission/SKILL.md and read by ahel’s review.
The last check before submitting through Elsevier Editorial Manager. Two things sink Cognitive Psychology submissions most often: a wrong-shape contribution (single effect, no model/theory, or a model that is never compared) and non-reproducible modeling (fits that can't be regenerated, no code deposit). Verify volatile specifics (length, abstract limit, review model, current editor, declarations) on the official guide for authors first (检索于 2026-06;以官网为准).
When to trigger
- "Submitting tomorrow" — last pass before upload
- Unsure what the scope, format, and declaration requirements demand
- Confirming the abstract, exhibits, model comparison, code deposit, and declarations are in order
Process facts (verify volatile items on the official page)
- Owner / publisher: Elsevier. (检索于 2026-06;以官网为准)
- Portal: Elsevier Editorial Manager (linked from the ScienceDirect guide for authors).
- Identity: a leading cognitive-science journal favoring longer, integrative, model-driven articles; multi-experiment programs combined with formal/computational modeling.
- Scope: attention, perception, memory, learning, language, categorization, reasoning, problem-solving, judgment and decision-making; modeling/neuroscientific approaches and substantive reviews welcome.
- Style: APA-style statistical reporting and references; Elsevier formatting via the guide for authors. Confirm the current reference style and any structured-abstract requirement.
- Open science: authors are strongly encouraged to share data, model/analysis code, and materials; complete the Elsevier research-data statement and declaration of competing interest.
- Review model / length / abstract limits: volatile — confirm single- vs. double-anonymized review, any word/length guidance, and the abstract limit on the live page. 待核实.
Preflight checklist
Scope & shape
- Contribution is a theoretical advance carried by a program (multi-experiment and/or a model)
- If a model is central, it is fit and compared to a rival under matched flexibility
- Not a single-effect / atheoretical paper better suited to a short-report venue
Front matter & format
- Abstract present (confirm length/structure on the official page); keywords included
- APA-style statistics (effect sizes + intervals; model-comparison criteria) and references
- Exhibits show observed data + model fit (not bars of means); model-comparison table included
- Manuscript follows Elsevier formatting/section conventions per the guide for authors
Modeling & disclosure
- Model comparison reported (AIC/BIC/BF or cross-validation) with free-parameter counts
- Parameter + model recovery reported
- Mixed/hierarchical structure where the design demands it, with diagnostics
- Confirmatory vs. exploratory clearly separated
Open science & declarations
- Data deposited + DOI + codebook (or justified restriction)
- Model/analysis code deposited; fits regenerate in a fresh session (run log)
- Materials deposited + DOI
- Elsevier research-data statement + competing-interest declaration + funding/contributions
- Preregistration linked where applicable
Worked micro-example — preflight verdict (illustrative)
Running the recognition-memory program through the gate the night before upload:
Shape: 3 experiments + UVSD vs. DPSD comparison → theoretical advance → PASS
Model: both models fit (matched flexibility); dBIC + BF reported;
parameter + model recovery included → PASS
Hierarchy: hierarchical Bayesian; R-hat ~ 1.00, ESS adequate → PASS
Exhibits: z-ROC figure overlays observed data + both model curves; model-
comparison table with free-parameter counts → PASS
Open sci: data + model code + materials each have a DOI; fits regenerate
in a fresh session (run log attached) → PASS
Declarations: competing interest (none) + research-data statement + funding
completed in Editorial Manager → PASS
Verdict: ready to upload to Editorial Manager.
Last-mile failure modes that trigger a return
| Failure | Caught by | Quick fix |
|---|---|---|
| Model fit but never compared | scope/shape check | fit the rival; add the comparison table |
| Fits don't regenerate from code | reproducibility check | deposit seeded code + a fresh-session run log |
| Bars of means, no model overlay | exhibit check | redraw with observed data + model fit |
| "Data on request" instead of a DOI | open-science check | deposit and mint a persistent identifier |
| Competing-interest/data statement blank | declaration check | complete the Elsevier declarations before upload |
Volatile specifics (length guidance, abstract limit, review model, current editor, exact declarations) change. Re-confirm every item above against the journal's current guide for authors before relying on it (检索于 2026-06;以官网为准).
Anti-patterns
- Submitting a single-effect/atheoretical paper to a model-driven, long-form venue
- A central model that is fit but never compared to a rival
- Modeling that cannot be reproduced from the deposited code
- Exhibits that hide the fit (bars of means) or assert "best fit" with no table
- Missing Elsevier research-data / competing-interest declarations
Output format
【Shape】theoretical advance via a program; model fit + compared? [Y/N]
【Format】abstract + keywords + APA-style reporting + Elsevier formatting? [Y/N]
【Modeling】comparison + recovery + hierarchy + diagnostics? [Y/N]
【Open science】data + model code (reproducible) + materials + DOIs? [Y/N]
【Declarations】competing interest + research-data + funding? [Y/N]
【Next】await decision → cogpsych-rebuttal on revision
Supplementary resources
templates/checklist.md— the eight-section pre-submission self-check../../resources/external_tools.md— repositories, DOIs, modeling/reproducibility tooling../../resources/official-source-map.md— official Cognitive Psychology / Elsevier URLs behind every fact in this pack
Signals
- GitHub stars
- 1k
- Forks
- 155
- Last commit
- Sep 2026
Advanced
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cogpsych-submission- Source
- github.com/brycewang-stanford/awesome-journal-skills
github.com/brycewang-stanford/awesome-journal-skills
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