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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when deciding whether a project fits Agricultural Systems (AgSy) and which article type to target. AgSy is a systems-science journal, so the test is a genuine systems question — interactions among components, across hierarchical levels (field → farm → landscape → region → food system), trade-offs, and emergent behavior — analyzed with integrated modelling, NOT a single-factor field trial. Helps frame the question; it does not collect data.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Agricultural Systems publishes the systems analysis of agricultural systems. The bar is not "a new result for crop X" — it is "a systems question about interactions and trade-offs." Use this skill to pressure-test fit before you invest, and to keep a field trial from being mistaken for a systems paper.
A strong AgSy paper usually clears all four:
agsy-impact-and-implications).| If your work is at… | reach AgSy fit by… |
|---|---|
| Field / plot | scaling to the farm or showing the field-level interaction that matters to the system |
| Whole-farm | the journal's sweet spot — show component interactions and whole-farm trade-offs |
| Landscape / region | spatial interactions, land-use competition, aggregation/emergence across farms |
| Food system | linking production to value chains, food security, environment, and policy |
agsy-review-process).Score the project against the four fit criteria, then read off the verdict.
| Systems Q | Scope | Trade-offs | Decision | Verdict |
|---|---|---|---|---|
| Yes | Yes | Yes | Yes | Strong AgSy fit — proceed |
| Yes | Field | Yes | Yes | Needs scaling: embed in a farm/landscape system |
| Yes | Yes | One optimum | Yes | Reframe: surface the trade-off across objectives |
| No | — | — | — | Off-fit — re-route to an agronomy/field-crops journal |
| Yes | Yes | Yes | No | Add the decision hook (agsy-impact-and-implications) |
When a project lands near the boundary, route it deliberately:
A team has trial data showing a legume intercrop raises maize yield:
【Question】one sentence (state the interaction / trade-off)
【System & boundary】components + hierarchical level(s) + scale
【Modelling approach】conceptual / empirical / dynamic / bio-economic
【Decision relevance】who acts differently if this is true
【Article type】Research paper / Short communication / Perspective / Comment / Review
【Fit verdict】strong / needs reframing / off-fit (why)
【Next】agsy-literature-positioning
../../resources/external_tools.md — systems models and data sources by scale../../resources/official-source-map.md — AgSy aims, scope, and article types아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.