{"id":"W2742657982","doi":"","title":"ブラウントラウト個体群(Salmo trutta)の生息密度の同調性に及ぼす河川流量,水理環境,水温,及び分散の影響","year":2016,"lang":"ja","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Salmo; Fishery; Biology; Fish <Actinopterygii>; Zoology; Ecology; Environmental science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001533419,0.0002287199,0.0001492213,0.0004069688,0.0005853885,0.0003646076,0.000256127,0.0004619102,0.003490274],"category_scores_gemma":[0.0001218514,0.000172462,0.0003368895,0.0002475744,0.0004272869,0.000256201,0.0003979063,0.000405788,0.001007028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005055913,"about_ca_system_score_gemma":0.000359714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01112274,"about_ca_topic_score_gemma":0.02086461,"domain_scores_codex":[0.9999365,0.000005423072,0.000004254098,0.00002069654,0.00001608887,0.000016998],"domain_scores_gemma":[0.9998788,0.00001483151,0.00003000628,0.000008039932,0.00003191363,0.0000363822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006732142,0.0001365808,0.01393948,0.0001279246,0.00006308519,0.0005854322,0.0003128257,0.0003328294,0.9647209,0.001058703,0.0005042978,0.01754469],"study_design_scores_gemma":[0.000334804,0.01042542,0.4258483,0.0001504829,0.00061939,0.003813041,0.005651588,0.006660668,0.5054399,0.004355103,0.03655397,0.0001472554],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914107,0.0005042299,0.001106955,0.0002995994,0.00005096749,0.00002497311,0.000177101,0.00005101996,0.006374388],"genre_scores_gemma":[0.9857916,0.0003370855,0.001576011,0.000410746,0.00001964063,0.00001637014,0.0002838422,0.00001263265,0.01155222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01112274,"threshold_uncertainty_score":0.02211601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01629138642911022,"score_gpt":0.2025142956721429,"score_spread":0.1862229092430327,"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."}}