{"id":"W1995866558","doi":"10.1139/cjfas-2013-0426","title":"Scaling up experimental trawl impact results to fishery management scales — a modelling approach for a “hot time”","year":2014,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Trawling; Environmental science; Scaling; Biomass (ecology); Scale (ratio); Fishing; Fishery; Benthic zone; Fisheries management; Ecology; Mathematics; Geography; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005289991,0.0008691641,0.0005971794,0.0006200904,0.0005525145,0.001098434,0.001645395,0.001027262,0.002457841],"category_scores_gemma":[0.01046323,0.0005021991,0.001267464,0.000796818,0.001021601,0.003521539,0.001470363,0.001936645,0.00024951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001381673,"about_ca_system_score_gemma":0.0007377666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002505526,"about_ca_topic_score_gemma":0.002757508,"domain_scores_codex":[0.9982424,0.0007463431,0.0001773144,0.0003668745,0.0003601266,0.0001069822],"domain_scores_gemma":[0.9930367,0.003353311,0.001004711,0.001985095,0.0004775361,0.0001426227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001345917,0.003146531,0.0457217,0.001469083,0.0009141876,0.0004772095,0.0009339833,0.5183933,0.19113,0.06753857,0.002773082,0.1661565],"study_design_scores_gemma":[0.0002421453,0.004244355,0.04200945,0.000170618,0.0004426747,0.0001788182,0.0005520365,0.7354892,0.1036166,0.101374,0.01144511,0.0002349049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3734111,0.0006039211,0.6141659,0.001118292,0.0002617597,0.001014764,0.0008072368,0.0006118843,0.008005089],"genre_scores_gemma":[0.8147656,0.0005812327,0.1804381,0.0004557261,0.00008956789,0.001762677,0.0003772271,0.0001180553,0.001411811],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005289991,"threshold_uncertainty_score":0.02797645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03599786693725392,"score_gpt":0.2617857398971797,"score_spread":0.2257878729599258,"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."}}