{"id":"W3118395365","doi":"10.48550/arxiv.2101.01134","title":"Does Invariant Risk Minimization Capture Invariance?","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Invariant (physics); Minification; Generalization; Population; Mathematics; Applied mathematics; Computer science; Mathematical optimization; Mathematical analysis","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007557048,0.001385072,0.00174421,0.0009238498,0.0005852554,0.00231569,0.001910693,0.00209096,0.004522647],"category_scores_gemma":[0.04477695,0.00066201,0.001165169,0.0008919961,0.004139799,0.005132311,0.003452301,0.004478516,0.001134608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001069547,"about_ca_system_score_gemma":0.001243436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002200434,"about_ca_topic_score_gemma":0.001451521,"domain_scores_codex":[0.9956055,0.002288602,0.0001627647,0.001002555,0.0006244493,0.000316115],"domain_scores_gemma":[0.9790051,0.01414928,0.002376297,0.003207911,0.0008643327,0.0003971335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005500519,0.00006847623,0.003701477,0.0002070038,0.0001660451,0.0001702629,0.0002505786,0.0832981,0.0009411769,0.8351008,0.006177238,0.0698638],"study_design_scores_gemma":[0.00001449749,0.00005504131,0.0008863188,0.00005267739,0.00002546751,0.00009699274,0.00004081773,0.2768174,0.000437672,0.7180269,0.003524667,0.00002162779],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01005024,0.0006393388,0.9809355,0.002364821,0.00008298668,0.00001817586,0.00009677574,0.0001736743,0.005638483],"genre_scores_gemma":[0.7589293,0.001888813,0.2266399,0.003111846,0.0008566863,0.0001979397,0.0004458726,0.0006310357,0.007298697],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007557048,"threshold_uncertainty_score":0.03996599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05027508467693582,"score_gpt":0.1792011599192614,"score_spread":0.1289260752423256,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}