데이터·AI 스킬

Use when running the final pre-submission preflight for Agricultural Systems (AgSy) via the current Elsevier submission path / Editorial Manager — article-type selection, abstract <= 250 words, Highlights, graphical abstract, CRediT and declaration-of-interest statements, funding/AI disclosures, reference style, and data/code/model availability. Final checks; it does not draft content.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when preparing the data, code, and model materials for an Agricultural Systems (AgSy) manuscript. AgSy applies Elsevier's research-data policy, which treats software, code, and models as research data — deposit them in a repository and cite/link them, or state why they cannot be shared. Covers model-description standards and exemptions. Prepares the materials; it does not waive requirements.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when running the final pre-submission preflight for AEJ: Economic Policy via the AEA online submission system — single-blind review front matter, JEL codes, submission and publication fees, format, the Data and Code Availability Statement, and disclosure. Final checks; it does not draft content.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when assembling the data and code deposit for an AEJ: Economic Policy manuscript to satisfy the AEA Data and Code Availability Policy and the AEA Data Editor's pre-publication reproducibility check. Builds the openICPSR deposit, README, and restricted-data access paths; it does not run the analysis or write the paper.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when assembling the data, code, and documentation package for an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript to pass the AEA Data and Code Availability Policy and the AEA Data Editor's pre-publication reproducibility check. Covers macro specifics (simulation/calibration code, restricted-access data); it does not write the analysis itself.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when running the final pre-submission preflight for an American Economic Journal: Applied Economics (AEJ: Applied) manuscript via the AEA ScholarOne system — single-blind review front matter, JEL codes, submission and publication fees, format, disclosures, and AEA data-policy readiness. Final checks; it does not draft content.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when running the final pre-submission preflight for the American Economic Journal: Macroeconomics (AEJ: Macro) via the AEA submission system — membership-scaled fee, JEL codes, PDF and length rules, ≤100-word abstract, disclosure statements, and data/code readiness. Final checks; it does not draft content.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when partitioning content between an Advanced Materials main text and its Supporting Information, ensuring the paper stands alone while extended data, full experimental detail, and secondary characterization live in the SI. Organizes the Supporting Information; does not write the main text.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when assembling the data and code replication package for an American Economic Journal: Applied Economics (AEJ: Applied) manuscript to pass the AEA Data and Code Availability Policy and the AEA Data Editor's pre-publication reproducibility check. Builds the openICPSR deposit and README; it does not run the analysis or write the paper.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when building and refining exhibits for an Administrative Science Quarterly (ASQ) manuscript — qualitative data structures and data-to-theory tables, process models, and quantitative tables. Designs exhibits; it does not run the analysis behind them.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when an AEJ: Economic Policy manuscript needs a framework that maps reduced-form estimates into a welfare, cost-benefit, or distributional policy object — sufficient statistics, MVPF, optimal-policy, or a small applied model. Builds the estimate-to-welfare bridge and states its assumptions; it does not run the empirical estimation or write the prose.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when executing and reporting the analysis for an Administrative Science Quarterly (ASQ) manuscript — qualitative coding and data-to-theory construction, or quantitative estimation and robustness. Makes the evidence-to-theory link transparent; it does not design the study (see asq-methods).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when organizing the ACM MM (ACM Multimedia) supplementary material due after the paper deadline — deciding what belongs in the 6-8 page body versus the supplement, packaging video/audio/interactive demos that render on a reviewer's machine, keeping all assets anonymous for double-blind tracks, and pointing to code and data.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when strengthening the reproducibility of an ACM MM (ACM Multimedia) paper or preparing for the ACM MM Reproducibility track and ACM artifact badging — capturing environments, media/data access, seeds, and multimodal pipelines so an independent reviewer can rebuild results and reach Artifacts Evaluated or Results Reproduced badges.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when choosing and justifying the research design for an Administrative Science Quarterly (ASQ) manuscript — qualitative (grounded-theory, ethnographic, historical) or quantitative — and setting the rigor bar. Designs the study; it does not run the analysis (see asq-data-analysis).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when strengthening ACM CCS reproducibility evidence, including the artifact-availability posture, threat-model-to-evidence mapping, attack reproduction steps, defense overhead measurement, measurement-dataset provenance, environment and version pinning, and honest justification when artifacts cannot be shared.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when packaging code, models, datasets, or media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release, and choosing between the Open Source Software Competition, the Dataset track, the Reproducibility track, and main-track supplementary evidence, each with its own blinding and expectations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when preparing the ACM MM (ACM Multimedia) camera-ready version of record — de-anonymizing safely, completing the ACM rights form and CCS concepts, meeting ACM sigconf requirements, releasing code/data/media artifacts and any earned reproducibility badge, registering, and planning the oral/poster presentation in Rio.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when analyzing the material of an Accounting, Organizations and Society (AOS) manuscript — coding and interpreting qualitative field data, estimating experimental and survey models, or running theory-laden archival analyses, with an audit trail appropriate to each tradition. Analyzes and reports; it does not design the study (aos-methods).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when building the theoretical engine of an Accounting, Organizations and Society (AOS) manuscript — choosing a social/organizational theory tradition (institutional theory, governmentality, Bourdieu, actor-network theory, practice theory, psychological process theory) and making it generate the analysis rather than decorate it. Builds the lens; it does not collect data (aos-methods) or frame the contribution (aos-contribution-framing).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when positioning an ACL submission against the NLP literature, covering ACL Anthology citation practice, arXiv-versus-published version citation, concurrent LLM-era preprints, prior-cycle ARR resubmission overlap, anonymity-preserving self-citation, and the fast-moving baseline problem in computational linguistics.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when revising an ACL paper for computational-linguistics house style, covering task-first framing, linguistic examples tied to quantitative error analysis, scoping language claims to tested languages, LLM-era claim discipline, anonymous self-reference, Limitations prose, and compressing into the 8-page or 4-page ACL format.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when building the conceptual exhibits of an Academy of Management Review (AMR) manuscript — process models, 2x2 typologies, multi-level frameworks, and propositions tables that carry theoretical work. These are CONCEPTUAL figures, NOT data plots; AMR has no charts of results because it has no data.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when articulating what an Accounting, Organizations and Society (AOS) manuscript contributes — converting findings into a claim that changes how the field understands accounting's social, organizational, behavioral or institutional operation. Frames the payoff; it does not produce new analysis (aos-data-analysis).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.