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 anticipating referee objections or calibrating review expectations for an American Economic Journal: Microeconomics (AEJ: Micro) manuscript before submission. Pre-empts the objections theory referees raise and reads the editorial process; it does not draft the response letter (see aejmic-rebuttal).
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
resources/official-source-map.md).| Likely objection | Pre-empt it by (skill) |
|---|---|
| "The result is a knife-edge artifact of assumption A." | Name the load-bearing assumption; show necessity / a counterexample on failure (aejmic-identification) |
| "This is too specialized / maximal-generality for AEJ: Micro." | Re-frame the broad-interest message; cut generality that hides it (aejmic-topic-selection, aejmic-theory-model) |
| "How does this differ from [closest result]?" | State the theorem-relative delta in one sentence (aejmic-literature-positioning) |
| "Does it survive [a continuum / asymmetry / perturbation]?" | Provide the earned extension or a clean negative result (aejmic-robustness) |
| "A step in the proof is asserted, not shown." | Complete the lemma scaffolding; self-contained proofs (aejmic-replication-package) |
| "The model is overloaded; the mechanism is invisible." | Reduce to the minimal environment; lead with intuition (aejmic-theory-model, aejmic-writing-style) |
| "This is an empirical paper, not theory." | Either restore the theoretical contribution or redirect to AEJ: Applied (aejmic-topic-selection) |
| (Applied) "Identification / inference is shaky; asterisks used." | Branch B/C identification; SEs not asterisks (aejmic-identification, aejmic-tables-figures) |
Before submitting a matching paper, the author lists likely objections: (1) "rides on substitutability" → already pre-empted in aejmic-identification with a counterexample; (2) "how does it differ from the deferred-acceptance literature?" → one-sentence delta ready; (3) "is the existence proof complete?" → lemma scaffolding done. The remaining risk is audience fit, so the intro is rewritten to foreground the broad market-design message rather than the technical condition. JEL codes C78/D47 route it to a market-design co-editor.
【Top 3 likely objections】[...] → 【Fix / owning skill】[...]
【Load-bearing assumption defended】[Y/N]
【Delta crisp】[Y/N] 【Broad-interest message explicit】[Y/N]
【Proof gaps closed】[Y/N]
【Routing】JEL codes [...] (single-blind — no anonymization)
【Venue confirmed】AEJ: Micro (not AEJ: Applied)? [Y/N]
【Next step】aejmic-submission
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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.
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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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