{"id":"W2067679457","doi":"10.1139/f09-028","title":"A generic model to estimate food consumption: linking von Bertalanffy’s growth model with Beverton and Holt’s and Ivlev’s concepts of net conversion efficiency","year":2009,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Aquaculture Nutrition and Growth","field":"Agricultural and Biological Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Allometry; Mathematics; Gadus; Applied mathematics; Whiting; Growth function; Statistics; Fishery; Ecology; Biology; Fish <Actinopterygii>","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":[0.001471103,0.001086973,0.0008100607,0.0008402822,0.0003397265,0.0009173877,0.002309037,0.001565686,0.001259977],"category_scores_gemma":[0.003754999,0.0004273969,0.001234384,0.001144676,0.0008205374,0.00156524,0.001021162,0.001263602,0.0005307989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001272937,"about_ca_system_score_gemma":0.0009346206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006987157,"about_ca_topic_score_gemma":0.00380607,"domain_scores_codex":[0.9994603,0.0001535154,0.00003462438,0.0001615648,0.0001424942,0.00004745477],"domain_scores_gemma":[0.9991647,0.0004341417,0.000140836,0.00008620823,0.0001485143,0.00002559309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001732988,0.00002836892,0.002094484,0.00009440979,0.00005388129,0.0001364325,0.000121716,0.8847726,0.002214846,0.08835423,0.001024453,0.0210872],"study_design_scores_gemma":[0.000003714004,0.00001637231,0.0005415501,0.000009272801,0.00001431935,0.00006918905,0.000009990268,0.9739233,0.0003687755,0.02316348,0.00186163,0.00001832123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00956689,0.0001829204,0.986878,0.000237908,0.00004383187,0.00004200146,0.0001587176,0.00009917603,0.002790599],"genre_scores_gemma":[0.4857954,0.001556997,0.4962479,0.0003590456,0.0001860918,0.0007318343,0.0009035456,0.0002141241,0.014005],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006987157,"threshold_uncertainty_score":0.01389295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03034408867212359,"score_gpt":0.2345730688259939,"score_spread":0.2042289801538703,"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."}}