Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
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Use when an American Economic Journal: Applied Economics (AEJ: Applied) decision letter arrives (R&R or conditional accept) and a response-to-referees letter plus a revision plan must be drafted. Plans and structures the response; it does not run the new analysis (aeja-identification / aeja-robustness) or the submission preflight.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
The editor's letter is the priority signal: it tells you which referee concerns are binding and which are optional. At AEJ: Applied the binding asks are almost always about design credibility (the identification, robustness, inference) before exposition. Address the editor's stated priorities first and in full; treat the referee reports as the menu the editor has already filtered. A revision is judged on whether the identification concerns are genuinely resolved, not on volume of new tables.
| Referee ask | Default response |
|---|---|
| Core identification doubt (binding per editor) | do it in full; show the new estimate + SE; update the paper |
| Robustness/inference request | run it; report stability of the point estimate |
| External-validity / estimand | add a calibrated scope statement; do not overclaim |
| Additional outcome/subgroup | run with MHT adjustment; or argue why it is out of scope |
| Exposition / framing | revise; cheap to do, builds goodwill |
| Out-of-scope new paper | respectfully decline with a one-line reason |
aeja-replication-package)Referee 2 says the staggered-DID estimate is biased and the parallel-trends story is thin; the editor's letter flags this as the binding concern. A weak response argues that TWFE "should be fine here." The AEJ: Applied response: re-estimate with Callaway–Sant'Anna, report the new ATT of 3.1pp (s.e. 0.9, vs. 3.6pp under TWFE), add the event-study leads and a Goodman-Bacon decomposition, and run an honest-DID bound — then in the letter quote the new number, cite the exact figure/table, and note the conclusion is unchanged but now robust. The editor sees the binding concern fully resolved with evidence, not assertion.
【Decision type】R&R / conditional accept / reject-and-resubmit
【Editor priorities】[binding asks, in order]
【Triage】done: [...] | partial: [...] | declined (with reason): [...]
【Decisive evidence】new identification/robustness result + number(SE) + location
【Tone check】gracious, concrete, evidence-based? [Y/N]
【Package sync】replication updated to match revision? [Y/N]
【Next step】aeja-submission (resubmit) → re-enter aeja-workflow if further rounds
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Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
中文简介正在准备中。当前显示原文说明。
Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.
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Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.
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Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.
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Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.
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Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.
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