{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002654629,0.0003620591,0.0003748228,0.0001708953,0.0002153336,0.000454778,0.001848366,0.0005076316,0.00006408858],"category_scores_gemma":[0.00009803415,0.0003119145,0.0001942432,0.0006438521,0.00008107886,0.0005512726,0.00193667,0.0009590327,0.00004477063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001458117,"about_ca_system_score_gemma":0.0005440388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007902633,"about_ca_topic_score_gemma":0.0002630594,"domain_scores_codex":[0.9974626,0.0003346587,0.0002507654,0.001465658,0.0001235587,0.0003627079],"domain_scores_gemma":[0.9974636,0.00009564631,0.0003600048,0.001561639,0.0003149541,0.0002041512],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002309582,0.0001809963,0.003612435,0.0001370924,0.0001997057,0.0009886216,0.001883962,0.6974475,0.00006142385,0.2932035,0.0006583161,0.00160333],"study_design_scores_gemma":[0.000277667,0.00001805149,0.0007548772,0.0001704331,0.00007669625,0.000005424955,0.0001550267,0.9293579,0.0001631517,0.0683028,0.0001637376,0.0005542068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04618716,0.00008897917,0.9504114,0.0002554078,0.00124358,0.0001715148,0.00002468001,0.0002830593,0.001334262],"genre_scores_gemma":[0.9811848,0.0006611217,0.01639934,0.000234336,0.000103532,0.000001378539,0.00004668163,0.00001850243,0.001350265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9349977,"threshold_uncertainty_score":0.9999333,"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."}}