{"id":"W2205918308","doi":"10.1111/faf.12134","title":"Prioritization of knowledge‐needs to achieve best practices for bottom trawling in relation to seabed habitats","year":2015,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Grieg Seafood (Canada)","funders":"European Commission; Seventh Framework Programme; Arcadia Fund; David and Lucile Packard Foundation","keywords":"Trawling; Fishing; Fishery; Environmental resource management; Business; Bottom trawling; Consistency (knowledge bases); Work (physics); Computer science; Environmental science; Engineering","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":[0.06981288,0.0007936959,0.001357661,0.0122336,0.003767559,0.007114469,0.002245012,0.00262479,0.004106861],"category_scores_gemma":[0.09580234,0.0007460627,0.001037152,0.005522127,0.001666754,0.005969511,0.007368396,0.002292444,0.000651497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01032354,"about_ca_system_score_gemma":0.03107609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007880736,"about_ca_topic_score_gemma":0.01090774,"domain_scores_codex":[0.960584,0.01704293,0.00550287,0.001366223,0.01038583,0.005118113],"domain_scores_gemma":[0.8436801,0.08938625,0.00991085,0.003734044,0.04097578,0.012313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001061083,0.001248849,0.1168498,0.01366539,0.0003813553,0.002866571,0.1812397,0.004250719,0.0162168,0.01882301,0.01822391,0.6251729],"study_design_scores_gemma":[0.0003793279,0.001853073,0.2462985,0.01142956,0.0005200465,0.002055075,0.5374677,0.0199386,0.01124903,0.06353807,0.1045713,0.0006996772],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8957607,0.002184608,0.03051475,0.02777892,0.0002255581,0.003579119,0.0009016111,0.0002892231,0.03876558],"genre_scores_gemma":[0.94149,0.0009082564,0.05346778,0.0006531159,0.00005743982,0.001133677,0.0005256392,0.00003157439,0.001732598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06981288,"threshold_uncertainty_score":0.3692102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06604518270146334,"score_gpt":0.3172369804871751,"score_spread":0.2511917977857118,"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."}}