{"id":"W2566628918","doi":"10.1139/cjfas-2016-0265","title":"Marine growth patterns of southern British Columbia chum salmon explained by interactions between density-dependent competition and changing climate","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Victoria; University of Guelph; Fisheries and Oceans Canada","funders":"","keywords":"Oncorhynchus; Pacific decadal oscillation; Competition (biology); Ocean gyre; Biomass (ecology); Productivity; Fishery; Range (aeronautics); Biology; Hatchery; Climate change; Environmental science; Oceanography; Sea surface temperature; Ecology; Fish <Actinopterygii>; Subtropics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000345484,0.0003343229,0.000279497,0.0005900681,0.0005479951,0.0004877899,0.0003379661,0.0002800008,0.001182841],"category_scores_gemma":[0.001013973,0.000333307,0.0003495052,0.0007936875,0.0004708902,0.0001426401,0.0003933783,0.0002814694,0.0002257211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00208706,"about_ca_system_score_gemma":0.001047096,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6376611,"about_ca_topic_score_gemma":0.8194602,"domain_scores_codex":[0.9997993,0.00003683651,0.00001171928,0.00004847557,0.00003530357,0.0000683885],"domain_scores_gemma":[0.9993352,0.0001176829,0.00015462,0.00005913889,0.0001343241,0.0001989163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006585332,0.00001331772,0.9968129,0.000003844168,0.00005703175,0.00005692563,0.000158146,0.0002821668,0.0008702356,0.00001369272,0.0001508734,0.001514967],"study_design_scores_gemma":[7.631331e-7,0.000004602089,0.9996923,7.209919e-7,0.000004523271,0.00000998913,0.00005766598,0.0001894361,0.000008936787,0.000003320056,0.00002631331,0.000001476977],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996376,0.00003426583,0.00001961127,0.000009648242,7.869211e-7,9.87864e-7,0.0001856167,0.00000307625,0.0001083154],"genre_scores_gemma":[0.9994007,0.00002360618,0.00002612059,0.000004749779,8.301392e-7,0.000002706169,0.0003660389,0.000001911888,0.0001732801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3623389,"threshold_uncertainty_score":0.7289456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00869495009397003,"score_gpt":0.185738985767367,"score_spread":0.177044035673397,"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."}}