{"id":"W2922056107","doi":"10.1139/cjfas-2018-0477","title":"Biologging in combination with biotelemetry reveals behavior of Atlantic salmon following exposure to capture and handling stressors","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Oceans Limited (Canada); Memorial University of Newfoundland; Ocean Tracking Network; Dalhousie University; Greenfield Research (Canada); Fisheries and Oceans Canada; Carleton University","funders":"","keywords":"Salmo; Fishery; Population; Fish <Actinopterygii>; Biology; Ecology; Environmental science; Zoology; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0001529791,0.000212046,0.0002226546,0.0003194815,0.0001960803,0.0002370869,0.0001209737,0.0002940093,0.0008093864],"category_scores_gemma":[0.0004148534,0.0001779429,0.000182471,0.0002001298,0.0002265635,0.0001759709,0.0002917136,0.0003400743,0.0002071145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001844946,"about_ca_system_score_gemma":0.0002007368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004932237,"about_ca_topic_score_gemma":0.01739155,"domain_scores_codex":[0.9998934,0.00001859979,0.000006256602,0.00002798855,0.00002887546,0.00002495953],"domain_scores_gemma":[0.9997625,0.00002618313,0.0000908295,0.00002055453,0.00003171772,0.0000683066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007839674,0.0002521245,0.7754686,0.00002860057,0.00004741194,0.00007509585,0.0004320497,0.0001047011,0.2134751,0.00001292174,0.00007956074,0.009239692],"study_design_scores_gemma":[0.000002403194,0.0004101324,0.9979759,9.640203e-7,0.000005914138,0.00002597661,0.0001045108,0.0001000846,0.001335195,0.000003470879,0.00003345533,0.000002111544],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997494,0.00002077015,0.00006275937,0.000004740139,0.000001313029,0.000003436725,0.00003940778,0.000001494646,0.0001168189],"genre_scores_gemma":[0.9988121,0.0000482257,0.0002425948,0.00002278944,0.000003819358,0.00002353076,0.0002186484,0.000001637134,0.0006266299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004932237,"threshold_uncertainty_score":0.00980705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009153030246434404,"score_gpt":0.2061540852716455,"score_spread":0.1970010550252111,"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."}}