{"id":"W7084066974","doi":"10.64628/aam.vpa7mudn9","title":"Artificial intelligence makes fishing more sustainable by tracking illegal activity","year":2019,"lang":"en","type":"article","venue":"","topic":"Fungal and yeast genetics research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Fishing; Tracking (education); Tracking system; Sustainability; Sustainable development","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004917059,0.0003729348,0.0001497519,0.001128447,0.0004625813,0.001887965,0.0005826214,0.001028606,0.005223576],"category_scores_gemma":[0.002040869,0.0001813237,0.0002892924,0.0007440942,0.001342485,0.002499503,0.0008345951,0.0007437539,0.001282763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004140344,"about_ca_system_score_gemma":0.0004975112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001559254,"about_ca_topic_score_gemma":0.002134976,"domain_scores_codex":[0.9996263,0.00008339366,0.00002117837,0.00008002295,0.0001571427,0.00003192901],"domain_scores_gemma":[0.9985827,0.0004283439,0.0003842677,0.0002274492,0.000248493,0.0001288088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002193569,0.0005513954,0.07473172,0.0005049699,0.0003053362,0.0005785268,0.0006175176,0.04756866,0.05585513,0.1399273,0.02747807,0.6516621],"study_design_scores_gemma":[0.00006621231,0.0003990486,0.06214954,0.0004858791,0.000320889,0.001090181,0.002710306,0.2791343,0.0471195,0.4151237,0.1912325,0.0001679312],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4127075,0.00191184,0.251338,0.01497146,0.001138969,0.0001090535,0.0006648984,0.002026211,0.315132],"genre_scores_gemma":[0.9173886,0.00149495,0.06010166,0.001046133,0.0002055267,0.00003582165,0.0004046187,0.00008669141,0.01923595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005223576,"threshold_uncertainty_score":0.01747459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01701334722333159,"score_gpt":0.2915838113237392,"score_spread":0.2745704641004076,"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."}}