{"id":"W4391451981","doi":"10.1093/jrssig/qmae008","title":"Down the Victorian data mine","year":2024,"lang":"en","type":"article","venue":"Significance","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Ingenuity; Loyalty; History; Political science; Law; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.0003177463,0.00006181578,0.00006162136,0.00001777127,0.00006582653,0.00006535531,0.0002481106,0.00002483013,0.0002434305],"category_scores_gemma":[0.0001564546,0.00003891623,0.00001812438,0.0001585628,0.00002533717,0.000117387,0.00004310995,0.00007852481,0.0001300006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001883985,"about_ca_system_score_gemma":0.00003121835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002937503,"about_ca_topic_score_gemma":0.0000725863,"domain_scores_codex":[0.9994307,0.00002596006,0.0001408761,0.0001703453,0.0001390936,0.00009308669],"domain_scores_gemma":[0.999051,0.000291022,0.00002882751,0.0005859468,0.0000219698,0.00002128331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007312062,0.00002776886,0.0005106552,0.00017154,0.00003203313,0.000008108106,0.001250047,0.00003790748,0.001003386,0.8536226,0.1311541,0.01217458],"study_design_scores_gemma":[0.00006042833,0.000008442151,0.002560141,0.00005434019,0.00003150217,0.000004553804,0.00002113313,0.02867151,0.0001466374,0.0783132,0.8900282,0.00009988721],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3013465,0.01081718,0.3368341,0.1130062,0.02307644,0.005206545,0.002317898,0.004154886,0.2032402],"genre_scores_gemma":[0.9939432,0.00001379263,0.003104045,0.00006263259,0.0005292161,0.00001128453,0.00007618908,0.00001366066,0.002246001],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7753094,"threshold_uncertainty_score":0.2665394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1157904213413293,"score_gpt":0.3711327314480455,"score_spread":0.2553423101067162,"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."}}