{"id":"W2396477456","doi":"10.1016/j.fishres.2016.04.018","title":"Best practices for catch-and-release recreational fisheries – angling tools and tactics","year":2016,"lang":"en","type":"article","venue":"Fisheries Research","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":285,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"National Institute of Food and Agriculture; Academy of Finland; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Fishing; Recreation; Catch and release; Recreational fishing; Fishery; Best practice; Fisheries management; Business; Diversity (politics); Bycatch; Environmental resource management; Ecology; Environmental science; Economics; Biology; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01134553,0.0007080333,0.0003965969,0.003025379,0.002231864,0.003080195,0.002587435,0.001494045,0.004274136],"category_scores_gemma":[0.01853783,0.0003495346,0.0005135341,0.001659991,0.001245569,0.003016296,0.002029497,0.001297063,0.001221582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002286146,"about_ca_system_score_gemma":0.00412024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00820379,"about_ca_topic_score_gemma":0.0394516,"domain_scores_codex":[0.988306,0.00509724,0.0009609049,0.0007895193,0.004070753,0.0007755252],"domain_scores_gemma":[0.9896609,0.0029163,0.001805236,0.001614234,0.002984388,0.001018966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001836636,0.00104609,0.03367279,0.0008958971,0.0001374221,0.0002696551,0.004252051,0.001962462,0.003325683,0.005171344,0.006774498,0.9423085],"study_design_scores_gemma":[0.0002529498,0.004499997,0.4750204,0.01662374,0.001100426,0.005296971,0.06374924,0.009128321,0.02244093,0.05926098,0.3420954,0.0005307392],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6058515,0.05268719,0.09256866,0.04800005,0.001327243,0.001108014,0.0006044926,0.0006685315,0.1971843],"genre_scores_gemma":[0.822683,0.01133334,0.1521761,0.001466257,0.0001722679,0.0004448688,0.0002692238,0.000112402,0.01134255],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01134553,"threshold_uncertainty_score":0.06000167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1759440265070155,"score_gpt":0.3737409664538393,"score_spread":0.1977969399468237,"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."}}