{"id":"W2724311541","doi":"10.1111/faf.12231","title":"What the past tells us about the future of Pacific salmon research","year":2017,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"University of British Columbia","keywords":"Fisheries science; Fishery; Rest (music); Face (sociological concept); Fisheries Research; Relevance (law); Fish <Actinopterygii>; Climate change; Aquaculture; Political science; Fisheries management; Oceanography; Sociology; Fishing; Law; Social science; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["sts"],"category_scores_codex":[0.0008993588,0.0001175111,0.000140557,0.00001659123,0.001627932,0.001044811,0.000968859,0.0000888152,0.003446958],"category_scores_gemma":[0.00009257752,0.00006154356,0.00004979773,0.0001269274,0.002802412,0.0007939559,0.001045096,0.0004214122,0.00003822593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001891925,"about_ca_system_score_gemma":0.00001298951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007861347,"about_ca_topic_score_gemma":0.001530425,"domain_scores_codex":[0.9984737,0.0001419346,0.0001606979,0.0002557413,0.0005703007,0.0003976033],"domain_scores_gemma":[0.9986755,0.0001562874,0.00007954687,0.0009718476,0.00003444431,0.0000823392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005483953,0.00002276054,0.7120554,0.00002004715,0.00001051686,0.000006347589,0.001424,2.433637e-7,0.0000680168,0.0001131695,0.1584405,0.1277841],"study_design_scores_gemma":[0.00006797332,0.00005635483,0.4177519,0.000005125492,0.000002291759,0.00000387639,0.002982626,0.00001421017,0.00006157575,0.0003760257,0.5786254,0.00005265353],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4984915,0.0001910358,0.000001703843,0.0405908,0.0004226208,0.0003687943,0.00001665104,0.00001291769,0.459904],"genre_scores_gemma":[0.9601896,0.007057609,0.00003240185,0.0004840384,0.0005645644,0.00005829184,0.000007708204,0.00002070555,0.03158506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4616981,"threshold_uncertainty_score":0.9999922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03199918080150178,"score_gpt":0.2849788230284517,"score_spread":0.25297964222695,"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."}}