{"id":"W2568502790","doi":"10.1139/cjfas-2016-0480","title":"Authorized net losses of fish habitat demonstrate need for improved habitat protection in Canada","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Environmental Conservation and Management","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Fisheries and Oceans Canada; Memorial University of Newfoundland","funders":"","keywords":"Habitat; Fishery; Fish habitat; Habitat destruction; Fish <Actinopterygii>; Scope (computer science); Authorization; Business; Fisheries management; Safe harbor; Government (linguistics); Fishing; Environmental resource management; Geography; Ecology; Environmental science; Law; Political science; Biology; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004616609,0.00007701987,0.0001516162,0.00005095902,0.0003947061,0.0001285161,0.0002731331,0.00002012046,0.00008813859],"category_scores_gemma":[0.0002435054,0.00006490225,0.00002684664,0.00008043931,0.0006642384,0.0004613417,0.00002469997,0.00005433146,3.420069e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001967533,"about_ca_system_score_gemma":0.0005210833,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8773727,"about_ca_topic_score_gemma":0.9973581,"domain_scores_codex":[0.9992397,0.00002360146,0.0002823447,0.0001179287,0.0001395753,0.0001968187],"domain_scores_gemma":[0.9993426,0.00004404227,0.0003317316,0.00009393314,0.000006598042,0.0001811349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002773878,0.00001093324,0.9596243,0.00002535092,0.00001230543,0.000008235378,0.000283189,0.0000953713,0.001864199,0.00007531287,0.006690806,0.03128224],"study_design_scores_gemma":[0.0007986869,0.0003947178,0.9711487,0.00007155514,0.00001774547,0.00001243144,0.002772979,0.00663681,0.0008575651,0.001808628,0.01530464,0.0001755924],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802016,0.00002158913,0.0002253291,0.01825484,0.0002165021,0.0002438292,0.000007672726,7.731277e-7,0.0008278886],"genre_scores_gemma":[0.9976215,0.00001633962,0.001611919,0.0005876602,0.00001074956,0.000006928896,4.605915e-7,0.000003211546,0.0001412196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1199854,"threshold_uncertainty_score":0.30358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02387527276529462,"score_gpt":0.2137050079972994,"score_spread":0.1898297352320048,"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."}}