{"id":"W4409605879","doi":"10.1111/sjos.12785","title":"Mode‐adaptive factor models","year":2025,"lang":"en","type":"article","venue":"Scandinavian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Social Sciences and Humanities Research Council of Canada; University of California, Riverside; University of Victoria; Purdue University","keywords":"Mathematics; Factor (programming language); Mode (computer interface); Statistics; Applied mathematics; Econometrics; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0003390408,0.000172948,0.0004674687,0.000181474,0.00008945078,0.00005117272,0.0002669333,0.00007539417,0.0002058168],"category_scores_gemma":[0.001676659,0.0001379906,0.00008172114,0.0002096445,0.0001289214,0.0001150365,0.00004413663,0.000349719,0.000004675671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001081888,"about_ca_system_score_gemma":0.0001790356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008897602,"about_ca_topic_score_gemma":0.000003276705,"domain_scores_codex":[0.9984218,0.0001459562,0.0007047275,0.0001315195,0.0003400397,0.0002559415],"domain_scores_gemma":[0.9968503,0.001831292,0.0003960388,0.0001814682,0.0005811102,0.0001598648],"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":[0.0000923727,0.00007245707,0.0002081864,0.00006358469,0.00009120197,0.00005399778,0.0002992878,0.00004423831,0.00006000855,0.9477829,0.009342449,0.04188927],"study_design_scores_gemma":[0.0005069377,0.0002723465,0.0006700572,0.0003035571,0.0001002154,0.00002482043,0.0001661528,0.01283619,0.000239005,0.9845806,0.0001647638,0.000135386],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003108309,0.0001038769,0.9888505,0.00008673184,0.0004921827,0.00009978337,0.0006252551,0.00001210824,0.006621292],"genre_scores_gemma":[0.3370197,0.00004407543,0.6622902,0.00006602651,0.00005511486,0.000001531419,0.000001021463,0.00001250234,0.0005098321],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3339114,"threshold_uncertainty_score":0.5627095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1275714976985549,"score_gpt":0.3942387830683169,"score_spread":0.2666672853697619,"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."}}