{"id":"W2003979414","doi":"10.1017/s0376892913000209","title":"Distinguishing benchmarks of biological status from management reference points: A case study on Pacific salmon in Canada","year":2013,"lang":"en","type":"article","venue":"Environmental Conservation","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Stakeholder; Socioeconomic status; Environmental resource management; Population; Geography; Management by objectives; Identification (biology); Process (computing); Term (time); Transparency (behavior); Fisheries management; Business; Environmental planning; Computer science; Fishery; Ecology; Political science; Environmental science; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.008974655,0.0003450188,0.0003663525,0.001319427,0.0102947,0.002861064,0.001545052,0.001360405,0.0008699304],"category_scores_gemma":[0.01591172,0.0002756413,0.0002912567,0.003436588,0.00317025,0.001035985,0.002183334,0.001657725,0.00008806553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05568773,"about_ca_system_score_gemma":0.0623665,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9792406,"about_ca_topic_score_gemma":0.9943733,"domain_scores_codex":[0.9938688,0.002469563,0.0002805961,0.0002836982,0.00198221,0.001115229],"domain_scores_gemma":[0.9885136,0.004652403,0.0005888961,0.0003046544,0.004991907,0.0009485037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005311552,0.0008132861,0.5405872,0.0007999038,0.0001355024,0.01345822,0.2090641,0.01448859,0.004262605,0.02232418,0.01343624,0.1800991],"study_design_scores_gemma":[0.00008720282,0.0005162937,0.3464316,0.0008183385,0.0001563628,0.001136499,0.570302,0.01858017,0.003245821,0.004303036,0.05421481,0.0002078309],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9773461,0.0005254426,0.002525844,0.003303402,0.0000219272,0.0003678143,0.0002759052,0.0000301109,0.01560344],"genre_scores_gemma":[0.9901619,0.0003947071,0.006469285,0.0004131651,0.000005217827,0.0001131127,0.0001464283,0.0000139168,0.002282353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05568773,"threshold_uncertainty_score":0.4040446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01982600399982113,"score_gpt":0.2067451254700061,"score_spread":0.186919121470185,"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."}}