{"id":"W2751107768","doi":"","title":"河川生息地,個体群密度,及び体サイズに関連したスチールヘッド稚魚の行動:個体の成長速度への影響","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":"Geography; Biology; Ecology","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":[0.003118806,0.0002990436,0.0002594834,0.001155886,0.003119123,0.005034663,0.0006664927,0.001700999,0.0115381],"category_scores_gemma":[0.006124816,0.0002750485,0.0002952641,0.0009688667,0.009512673,0.004144953,0.001279936,0.001614447,0.001425029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004558588,"about_ca_system_score_gemma":0.005451886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03301505,"about_ca_topic_score_gemma":0.03828311,"domain_scores_codex":[0.9988009,0.0002193075,0.00008129304,0.0002548268,0.0004794408,0.0001642324],"domain_scores_gemma":[0.9976978,0.0007276161,0.0002994371,0.0001659389,0.0008479467,0.000261198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001357508,0.00009491877,0.01577625,0.0002939385,0.00003742023,0.0005598122,0.01357223,0.0006959426,0.001716558,0.7852522,0.01752643,0.1643385],"study_design_scores_gemma":[0.00004211532,0.0001342554,0.04106513,0.0005542508,0.0001097159,0.001004759,0.02532911,0.001633664,0.003355607,0.5685323,0.3581243,0.0001147922],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1585648,0.02625148,0.0323276,0.05152975,0.002070872,0.0001537907,0.00042164,0.00009893895,0.7285812],"genre_scores_gemma":[0.932109,0.005608829,0.009638972,0.002044979,0.0005265262,0.00005187794,0.0000850229,0.00002915147,0.04990561],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03301505,"threshold_uncertainty_score":0.06564575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01626834801887244,"score_gpt":0.1992518366104869,"score_spread":0.1829834885916144,"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."}}