1,109 件 ・ 関連度順
概要と使いどころ
Use when building or revising the exhibits of an American Economic Journal: Applied Economics (AEJ: Applied) manuscript so the main causal result is legible in one table or figure and respects AEA house presentation norms. Formats exhibits; it does not establish the result (aeja-identification / aeja-robustness) or write the surrounding prose.
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 deciding which aeja-* sub-skill to invoke next, or when sequencing manuscript work from topic selection through rebuttal for an American Economic Journal: Applied Economics (AEJ: Applied) submission. Routes — it does not replace — the specialized skills.
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 revising the prose, abstract, and introduction of an American Economic Journal: Applied Economics (AEJ: Applied) manuscript so the design and headline estimate land in the first paragraph in AEA house style. Polishes exposition; it does not change the result (aeja-identification / aeja-robustness) or the exhibits.
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 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.
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 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.
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 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.
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 an American Economic Journal: Applied Economics (AEJ: Applied) manuscript's headline estimate must be shown to survive specification, sample, and inference choices before submission or in an R&R. Builds the robustness suite a sophisticated referee expects; it does not establish the primary identification (aeja-identification) or format the exhibits (aeja-tables-figures).
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 an American Economic Journal: Macroeconomics (AEJ: Macro) decision letter has arrived (R&R or reject-with-comments) and you need a response-letter strategy and revision plan. Plans the rebuttal and revision; it does not run new identification, model, or robustness work itself (route to those skills).
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 anticipating the objections referees and coeditors will raise on an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript, and calibrating desk-reject and revision odds, before submission. Pre-empts pushback and plans the review; it does not draft the post-decision response letter (use aejmac-rebuttal).
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 the headline result of an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript must be shown stable across specification, sample, identification, and tuning choices. Builds the robustness program a macro referee will demand; it does not establish the primary identification or model (use aejmac-identification / aejmac-theory-model first).
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 an American Economic Journal: Applied Economics (AEJ: Applied) manuscript needs a model to interpret, discipline, or structure its empirical estimates — not to lead the paper. Calibrates how much theory belongs in an empirical-first journal and where it goes; it does not design the identification (aeja-identification) or build a standalone structural estimation.
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 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.
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 the empirical identification of a macro shock or dynamic causal effect is the bottleneck for an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript — SVAR, local projections, narrative, high-frequency/proxy-VAR, or micro-data macro designs. Stress-tests the identification to the AEJ: Macro broad-interest quantitative bar; for model-parameter identification see aejmac-theory-model.
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 the contribution of an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript relative to the macro frontier is fuzzy, contested, or undersold. Frames the marginal contribution against quantitative-theory and identified-empirical literatures; it does not fix the identification or the model itself.
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 deciding whether a project fits AEJ: Economic Policy rather than J. Public Economics, AEJ: Applied, or AER, and when sharpening the policy question and its welfare stake for an AEJ: Economic Policy manuscript. Frames fit and the policy-question-first contribution; it does not design the identification or run estimation.
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 anticipating the objections a sophisticated American Economic Journal: Applied Economics (AEJ: Applied) referee will raise, so a manuscript pre-empts them before submission or addresses them in revision. Plans the defense; it does not draft the response letter (aeja-rebuttal) or run the submission preflight (aeja-submission).
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 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.
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 the marginal contribution of an American Economic Journal: Applied Economics (AEJ: Applied) manuscript is fuzzy or undersold and must be staked precisely against prior applied-micro work. Positions the contribution; it does not fix the identification (aeja-identification) or the prose (aeja-writing-style).
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 deciding whether an applied-micro project belongs at the American Economic Journal: Applied Economics (AEJ: Applied) rather than AER, AEJ: Economic Policy, or a field journal, and what its central question should be. Sets venue fit and question scope; it does not design the identification (see aeja-identification).
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。
Search and visualize the world's data - get charts, insights, and embeddable knowledge cards for finance, economics, demographics, sports, and more
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。
Tracks ctDNA across serial liquid-biopsy timepoints for molecular residual disease (MRD) and treatment-response monitoring, treating MRD as a binary integrated detection call across the patient's full variant set (with a defined LoD95 and per-sample specificity) rather than a per-timepoint VAF threshold, and handling undetectable samples as left-censored at the per-sample limit of detection rather than true zeros. Covers tumor-informed bespoke vs tumor-naive design, landmark vs surveillance sampling, molecular-response definitions and their non-standardization, censoring-aware clearance kinetics, and the multiple-testing structure of repeated surveillance. Use when monitoring ctDNA during therapy, calling molecular relapse before imaging, or estimating clearance half-life from serial samples.
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。
Identify tumor neoantigens from somatic variants with pVACtools (pVACseq/pVACfuse/pVACbind/pVACvector/pVACview) for personalized cancer vaccines and checkpoint biomarkers. Encodes the field's hard truth that binding prediction is the easy, near-solved part and single-digit-percent PPV lives downstream — so it centers clonality/CCF, HLA LOH (the silent invalidator), expression, proximal-variant phasing, agretopicity/foreignness quality, and the predicted->presented->immunogenic validation tiers. Use when nominating vaccine targets, ranking neoantigens, or building a tumor-to-candidate pipeline. Binding details in mhc-binding-prediction; ranking in immunogenicity-scoring.
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。
Predict peptide-MHC class I binding and natural presentation with MHCflurry, NetMHCpan-4.1, and MixMHCpred to nominate candidate CD8 T-cell epitopes. Covers the binding-affinity (BA) vs eluted-ligand (EL/presentation) distinction, why %Rank beats raw nM for cross-allele work, the MS abundance bias that misranks low-expression neoantigens, allele-coverage inequity, and length bias. Use when scanning a protein or peptide set for class I epitopes, scoring neoantigen candidates, or choosing a binding predictor. For CD4/HLA class II see mhc-class-ii-prediction.
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。
Discovers, classifies, filters, and quantifies full-length transcript isoforms from PacBio Iso-Seq/Kinnex (HiFi) and Oxford Nanopore (cDNA/direct-RNA) long reads, using the isoseq+pigeon pipeline, SQANTI3, and ONT tools (IsoQuant, FLAIR, Bambu, StringTie2). Covers why a novel isoform is an artifact until proven otherwise (RT template-switching, intra-priming, and 5' degradation manufacture junctions and truncations), the SQANTI3 structural categories and their trust order, the Kinnex skera-split step, orthogonal CAGE/poly-A/short-read-junction validation, and why long-read isoform quantification needs EM. Use when building a full-length isoform catalog, classifying/filtering long-read transcripts, running Iso-Seq or ONT cDNA/dRNA analysis, or judging novel-isoform reliability.
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。