{"id":"W1988418425","doi":"10.1016/j.aquaculture.2009.06.021","title":"A mathematical model to explain variations in estimates of starch digestibility and predict digestible starch content of salmonid fish feeds","year":2009,"lang":"en","type":"article","venue":"Aquaculture","topic":"Aquaculture Nutrition and Growth","field":"Agricultural and Biological Sciences","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"United Soybean Board","keywords":"Starch; Food science; Biology; Raw material; Animal science; Ecology","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":[0.001090533,0.0007154093,0.0007188435,0.000592046,0.0004625143,0.0009359765,0.001341941,0.00147477,0.00228297],"category_scores_gemma":[0.004386829,0.0005422418,0.0008970594,0.0006442911,0.0005898327,0.00136236,0.0008386936,0.001105237,0.0004174513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001002438,"about_ca_system_score_gemma":0.001015821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01128591,"about_ca_topic_score_gemma":0.005047854,"domain_scores_codex":[0.9998204,0.00005261994,0.0000130285,0.0000534387,0.00003286264,0.00002770608],"domain_scores_gemma":[0.9986023,0.0009500386,0.0001755855,0.0000408956,0.0001954896,0.0000357145],"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":[0.00001420855,0.0000199672,0.0007616903,0.00002855653,0.0000216702,0.00005782167,0.00003607269,0.9817684,0.0008029731,0.01305962,0.000389704,0.003039329],"study_design_scores_gemma":[0.000004277274,0.000006006436,0.0001783882,0.000002267319,0.000005574128,0.0000119628,0.000003151747,0.996825,0.00008546728,0.002713805,0.0001595389,0.000004609302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1062028,0.0005376746,0.8837894,0.001276473,0.0001258374,0.00005999163,0.0004866912,0.0002412501,0.007279978],"genre_scores_gemma":[0.9128239,0.0006229606,0.06933832,0.0002268111,0.0001185705,0.0003973219,0.0005164234,0.0001577205,0.01579795],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01128591,"threshold_uncertainty_score":0.02244043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04477987969239407,"score_gpt":0.2667895042444777,"score_spread":0.2220096245520837,"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."}}