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.
日本語の概要は準備中です。原文の説明を表示しています。
Use when calibrating expectations for the fast, decisive American Economic Review: Insights (AER: Insights) review process — conditional-accept-or-reject decisions, the single-round model, and pre-empting the objections a short paper cannot afford. Explains the process and stress-tests the paper; it does not write the response letter (see aeri-rebuttal).
インストールする前に、エージェントに与えられる指示の中身を確認できます。
AER: Insights runs single-blind AEA peer review: authors are visible to referees, while referees remain anonymous to authors. It is deliberately fast and decisive:
Strategic implication: because there is no R&R to fix things later, the paper must be submission-ready and objection-proofed up front. You get essentially one substantive look. A weak design, an overclaim, or a missing key check that an AER R&R would let you repair will instead produce a reject here.
A short paper has no room to answer everything during review, so answer the decisive objections before submitting:
| Likely objection | Pre-empt before submission |
|---|---|
| "Not important / not general interest" | Lead with the surprise and the prior overturned (aeri-topic-selection) |
| "Already known / incremental" | Confront the closest paper directly (aeri-literature-positioning) |
| "Design not credible" | Put the single strongest diagnostic in-text (aeri-identification) |
| "Result not robust" | One in-text check + a signposted appendix battery (aeri-robustness) |
| "Overclaimed" | Calibrate the claim to exactly what is identified |
Use the venue-neutral reviewer-objection-checklist to stress-test the design by identification strategy before drafting the final version.
【Process understood】conditional-accept/reject, no R&R, ~8wk conditional window? [Y/N]
【Decisive objections pre-empted】importance / novelty / design / robustness / claims
【Submission-ready】no key check deferred to a nonexistent round? [Y/N]
【Caps met】word + exhibit limits satisfied (no auto-return)? [Y/N]
【Fallback venue】<AEJ or field journal if reject>
【Next step】aeri-submission
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概要と使いどころ
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。