{"id":"W2136449392","doi":"10.1890/es14-00479.1","title":"Phylogenetics to help predict active metabolism","year":2015,"lang":"en","type":"article","venue":"Ecosphere","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Phylogenetic tree; Phylogenetics; Biology; Trait; Phylogenetic comparative methods; Ecology; Variable (mathematics); Statistics; Computer science; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001581936,0.001334303,0.0009900781,0.002006853,0.0006096091,0.001146725,0.0009002862,0.0009686508,0.00358802],"category_scores_gemma":[0.008109409,0.0007310249,0.001459718,0.001274246,0.0004898877,0.001665561,0.001036242,0.001467722,0.001249233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007356229,"about_ca_system_score_gemma":0.0004528161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006023952,"about_ca_topic_score_gemma":0.004770205,"domain_scores_codex":[0.9994146,0.0002606697,0.00003146318,0.0001911293,0.0000637675,0.00003848631],"domain_scores_gemma":[0.9975604,0.001647103,0.0002530456,0.0002576912,0.0002058516,0.0000758762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001884485,0.0000922459,0.06903879,0.0001373354,0.0004278195,0.0002194616,0.0003319355,0.8032951,0.007411201,0.01088604,0.002064314,0.1059073],"study_design_scores_gemma":[0.000008346917,0.0000292738,0.00990524,0.00002539954,0.00004552273,0.00006718552,0.00002986071,0.9735303,0.000601857,0.01375861,0.001973353,0.00002493032],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1847185,0.00121688,0.8060612,0.0008301311,0.0001096162,0.00004534768,0.001287623,0.001647172,0.004083548],"genre_scores_gemma":[0.8627419,0.0005234004,0.1327684,0.0001537107,0.00009249179,0.0001062606,0.001584418,0.0003874722,0.001641946],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006023952,"threshold_uncertainty_score":0.01200312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01241416970265682,"score_gpt":0.2158993479492947,"score_spread":0.2034851782466379,"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."}}