{"id":"W1981452113","doi":"10.1162/002219500552081","title":"A Predatory Social Structure: Informers in Westminster, 1737-1741","year":2000,"lang":"en","type":"article","venue":"The Journal of Interdisciplinary History","topic":"Historical Economic and Social Studies","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Sociology; Sample (material); Criminology; Computer security; Political science; Business; Geography; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006526976,0.0001504177,0.0005068539,0.0001940809,0.0002252298,0.000008685588,0.0004481552,0.0001066969,0.002965504],"category_scores_gemma":[0.00002426095,0.0001297241,0.000208841,0.0001032322,0.0002827323,0.0003365774,0.0001116679,0.0004524693,0.000168405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002257733,"about_ca_system_score_gemma":0.00007383257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007490307,"about_ca_topic_score_gemma":0.0001346108,"domain_scores_codex":[0.9985265,0.00004224007,0.001016705,0.0001238338,0.00005514462,0.0002355904],"domain_scores_gemma":[0.999122,0.00005764775,0.0005896005,0.000139254,0.000027435,0.00006409457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002079085,0.00063109,0.00808069,0.0001389857,0.0006430621,0.00009772929,0.3947435,0.00127179,0.00007435341,0.02190744,0.5208294,0.04950286],"study_design_scores_gemma":[0.001140157,0.0003388276,0.02217343,0.00003565747,0.00002112558,0.00004797915,0.00296158,0.000127989,0.000002309018,0.0153835,0.9574413,0.0003261746],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8553096,0.01287169,0.00007128471,0.001395778,0.001718658,0.0001226467,0.00003671641,0.00001210003,0.1284615],"genre_scores_gemma":[0.9930338,0.0003636928,0.00004488556,0.0003703625,0.0004146153,0.00000224116,0.000001156653,0.00001804728,0.005751225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4366118,"threshold_uncertainty_score":0.9979459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02502631333004386,"score_gpt":0.2273467816059332,"score_spread":0.2023204682758893,"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."}}