{"id":"W6889525710","doi":"10.25549/webster-c100-12057","title":"Command Facts Handbook Chicago Police Department, 1992","year":2021,"lang":"en","type":"dataset","venue":"University of Southern California Digital Library","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Commission; Law enforcement; Newspaper; Criminal justice; Variety (cybernetics); Economic Justice","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004054866,0.0003350763,0.0004631231,0.0001384377,0.0002055479,0.0004201482,0.001435276,0.0002265623,0.0007219364],"category_scores_gemma":[0.0000122915,0.0003433512,0.0002813565,0.000262674,0.0001877672,0.0007003187,0.001393336,0.0002615589,0.002914615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002673257,"about_ca_system_score_gemma":0.0002232219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002281788,"about_ca_topic_score_gemma":0.00004332797,"domain_scores_codex":[0.9985206,0.00009551827,0.0002200681,0.0005270574,0.0003098627,0.0003269045],"domain_scores_gemma":[0.9985638,0.0001153295,0.0002672268,0.0007854215,0.00004034504,0.0002278801],"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":[0.00002063427,0.0001064232,0.00008005277,0.0000431822,0.0001149004,0.00008087367,0.00005324981,0.00004275832,0.000002583088,0.000002981277,0.9980962,0.001356206],"study_design_scores_gemma":[0.0003047032,0.00003044317,0.000004721426,0.0001286156,0.00004367969,0.000007555858,0.000181936,0.0002437248,0.00009390853,0.00009476912,0.9985206,0.000345306],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000443255,0.0003116204,0.01183535,0.0002575986,0.00007136942,0.0001428601,0.9860942,0.00008152422,0.001161144],"genre_scores_gemma":[0.0002790238,0.0002060948,0.002051203,0.0002819754,0.0001448277,2.720198e-7,0.9962146,0.00002105214,0.0008010045],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01012034,"threshold_uncertainty_score":0.9999018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007940943024841758,"score_gpt":0.1673093175859873,"score_spread":0.1593683745611456,"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."}}