{"id":"W2063959456","doi":"10.1080/00288330909510014","title":"Statistical fraud detection in a commercial lobster fishery","year":2009,"lang":"en","type":"article","venue":"New Zealand Journal of Marine and Freshwater Research","topic":"Benford’s Law and Fraud Detection","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dartmouth General Hospital","funders":"","keywords":"Homarus; American lobster; Fishery; Fishing; Benford's law; Geography; Crustacean; Biology; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01827232,0.0002399256,0.0005313276,0.0026326,0.0006075624,0.001445317,0.0009197004,0.0009965065,0.0008091303],"category_scores_gemma":[0.1041545,0.0002123714,0.0003935503,0.002193925,0.002083466,0.001492311,0.0008685581,0.0008903192,0.0001276731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002048102,"about_ca_system_score_gemma":0.0008243957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01288058,"about_ca_topic_score_gemma":0.006447751,"domain_scores_codex":[0.9899092,0.005532588,0.0007260991,0.000912183,0.002436251,0.0004837563],"domain_scores_gemma":[0.8168868,0.1416321,0.02536893,0.007853361,0.007447101,0.000811659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001937045,0.0000565345,0.9587971,0.00002743522,0.00007608601,0.0004220276,0.00042203,0.0149839,0.0006557591,0.004596576,0.0005089224,0.01925987],"study_design_scores_gemma":[0.00002552552,0.0001917869,0.4709581,0.00004617048,0.00003567016,0.001325063,0.0005598235,0.5120248,0.001959207,0.01194973,0.0008844061,0.00003978376],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981156,0.0001360181,0.01715255,0.0004983675,0.00001016296,0.00002595788,0.00009552627,0.00004997237,0.0008754976],"genre_scores_gemma":[0.9979809,0.00001495713,0.001828848,0.00002216611,0.000006015885,0.000005928352,0.00005319742,0.000001899833,0.00008604296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01827232,"threshold_uncertainty_score":0.09663439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08012537833989611,"score_gpt":0.365225366616062,"score_spread":0.2850999882761659,"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."}}