{"id":"W4389109428","doi":"10.32866/001c.90056","title":"Patterns in Bike Theft and Recovery","year":2023,"lang":"en","type":"article","venue":"Findings","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Variety (cybernetics); Identity theft; Computer security; Internet privacy; Business; Computer science; Artificial intelligence","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":[0.0004039223,0.00003632913,0.00006077192,0.00006990098,0.0001084868,0.00003782055,0.00008454841,0.00004545771,0.000180869],"category_scores_gemma":[0.0000415142,0.0000339982,0.00001823782,0.0002948479,0.00004205802,0.0001621057,0.00001466722,0.00006101538,0.00004291319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001937751,"about_ca_system_score_gemma":0.000021867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002535316,"about_ca_topic_score_gemma":0.007656747,"domain_scores_codex":[0.9995039,0.00001975594,0.00007695535,0.0001268184,0.0001015279,0.000171115],"domain_scores_gemma":[0.9998394,0.0000549087,0.0000132973,0.00005143827,0.000006124654,0.00003487611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002433341,0.000005075876,0.9922076,0.000005928337,9.909043e-7,0.000005777546,0.005230098,1.731124e-7,0.00002565615,0.0002436969,0.0004977377,0.001774844],"study_design_scores_gemma":[0.000073123,0.000005193041,0.9881517,0.00001523165,0.000001313447,2.471445e-8,0.0009116165,0.00000354154,0.00003247894,0.002607611,0.008149206,0.00004900495],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926911,0.00001607738,0.000004130857,0.0007876537,0.0001358437,0.00006555043,0.000008946087,0.00006387912,0.006226834],"genre_scores_gemma":[0.9965006,0.0000675156,0.0000075868,0.00006862547,0.00005266178,0.000003983764,0.000005819063,0.000003411589,0.003289761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007651468,"threshold_uncertainty_score":0.4272644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02761083574572935,"score_gpt":0.2997458418352105,"score_spread":0.2721350060894811,"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."}}