{"id":"W58106089","doi":"10.20381/ruor-20531","title":"Inferring and Revising Theories with Confidence: Analyzing the 1901 Canadian Census","year":2000,"lang":"en","type":"article","venue":"uO Research (University of Ottawa)","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Census; Genealogy; Epistemology; History; Sociology; Population; Demography; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00724991,0.000447389,0.0004819133,0.002496281,0.002956182,0.003189365,0.002213562,0.0007389213,0.003874202],"category_scores_gemma":[0.1254085,0.0004747031,0.0005353555,0.006047124,0.002881091,0.002153988,0.001416368,0.001817821,0.0002916497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02917847,"about_ca_system_score_gemma":0.02909342,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.984989,"about_ca_topic_score_gemma":0.9848055,"domain_scores_codex":[0.9976315,0.0006931323,0.0001016674,0.0003236197,0.0008987335,0.0003512967],"domain_scores_gemma":[0.9397988,0.03957976,0.00359359,0.004134627,0.01209789,0.0007954829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003683124,0.0001644663,0.6327012,0.0002574228,0.000303125,0.000324647,0.02241188,0.05342194,0.0005826965,0.09197607,0.03065532,0.1668329],"study_design_scores_gemma":[0.00006914333,0.00004400449,0.6321528,0.0003026599,0.000282184,0.0001289947,0.02209231,0.20856,0.001484194,0.0751332,0.05956291,0.00018765],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9583179,0.001855493,0.01242238,0.004565179,0.00004660244,0.000106785,0.005094985,0.0001256412,0.01746496],"genre_scores_gemma":[0.988396,0.0005590162,0.006400733,0.0001433147,0.00002107059,0.00003191224,0.002902832,0.00006065637,0.001484439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02917847,"threshold_uncertainty_score":0.2117056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07834340677087391,"score_gpt":0.3392559189037782,"score_spread":0.2609125121329043,"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."}}