{"id":"W3208545340","doi":"10.1163/15718085-bja10074","title":"New Scientific Information Can Help to Inform the Evaluation of EU Deep-sea Fisheries Regulations","year":2021,"lang":"en","type":"article","venue":"The International Journal of Marine and Coastal Law","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada","funders":"","keywords":"Fisheries management; European union; Fishery; Business; Commission; European commission; Fish stock; Fisheries science; Climate change; Marine ecosystem; Environmental resource management; Environmental planning; Ecosystem; Geography; Fishing; Oceanography; Environmental science; Ecology; International trade","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":[0.1642295,0.001388486,0.00201815,0.03568823,0.00272592,0.02071213,0.003698413,0.008444082,0.03548418],"category_scores_gemma":[0.2813569,0.0006081855,0.002373764,0.01909723,0.00396664,0.02066466,0.007732193,0.007758366,0.009891585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01024074,"about_ca_system_score_gemma":0.02166303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01064039,"about_ca_topic_score_gemma":0.01173812,"domain_scores_codex":[0.9047632,0.03663823,0.01304537,0.003937868,0.03889576,0.002719578],"domain_scores_gemma":[0.5566894,0.2401421,0.03642148,0.02758385,0.1330243,0.006138902],"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":[0.000301387,0.0004166189,0.01346145,0.005752923,0.0003697516,0.0005813178,0.00201695,0.003640103,0.001570296,0.2023269,0.3486766,0.4208857],"study_design_scores_gemma":[0.00005178107,0.0001341094,0.00773,0.0110741,0.0002327098,0.0001027636,0.002386547,0.001326999,0.001625203,0.09016656,0.88502,0.0001492629],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01851854,0.05309469,0.06219155,0.3275523,0.02042269,0.001644741,0.0392253,0.001389704,0.4759604],"genre_scores_gemma":[0.3453438,0.1021658,0.2794091,0.1354218,0.01255764,0.004581235,0.07107513,0.0011828,0.04826262],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1642295,"threshold_uncertainty_score":0.8685392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02367368954066535,"score_gpt":0.2714908958475296,"score_spread":0.2478172063068643,"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."}}