{"id":"W2767400871","doi":"10.1080/03632415.2017.1377558","title":"Fish Bioenergetics 4.0: An R-Based Modeling Application","year":2017,"lang":"en","type":"article","venue":"Fisheries","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":208,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"U.S. Geological Survey; U.S. Fish and Wildlife Service; Ipsen; South Dakota State University","keywords":"Bioenergetics; Fish <Actinopterygii>; Computer science; Ecology; Range (aeronautics); Environmental science; Biology; Fishery; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003738186,0.001771109,0.00112727,0.001667057,0.0005511809,0.001276852,0.003119348,0.0009302691,0.03420799],"category_scores_gemma":[0.009790927,0.001233017,0.001827184,0.0009441673,0.000499632,0.001205862,0.003479138,0.001898246,0.01785696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006727082,"about_ca_system_score_gemma":0.001842117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003685583,"about_ca_topic_score_gemma":0.002933675,"domain_scores_codex":[0.9988278,0.0003584484,0.0001194826,0.0002318195,0.0003745655,0.00008794864],"domain_scores_gemma":[0.9968748,0.00189466,0.0002229013,0.0003496862,0.0004905806,0.0001672906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001211383,0.0002747314,0.01476021,0.002701025,0.001060568,0.001462522,0.0009169249,0.1066169,0.03162688,0.02909824,0.624415,0.1858556],"study_design_scores_gemma":[0.0008511083,0.0003290842,0.007384962,0.0004993216,0.00040938,0.001034964,0.0001109521,0.4395049,0.02999741,0.03182576,0.4876468,0.0004053259],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009693527,0.0003463383,0.5966994,0.001023001,0.0002809865,0.0003859444,0.02085668,0.3630853,0.007628844],"genre_scores_gemma":[0.09451707,0.0008522443,0.7050348,0.001338418,0.0001882443,0.002652879,0.03514868,0.1468604,0.01340736],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03420799,"threshold_uncertainty_score":0.1144372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02241676367319942,"score_gpt":0.2389988206865807,"score_spread":0.2165820570133812,"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."}}