{"id":"W2994079203","doi":"","title":"DISCRIMINATION AND CLASSIFICATION OF POULTRY FEEDS DATA","year":2013,"lang":"en","type":"article","venue":"Journal of Mathematics Research","topic":"Protein Hydrolysis and Bioactive Peptides","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linear discriminant analysis; Mathematics; Discriminant function analysis; Discriminant; Statistics; Pattern recognition (psychology); Artificial intelligence; Computer science","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":[0.00145925,0.0005549306,0.0005283499,0.00333555,0.0003472841,0.0006748539,0.0003599715,0.0004981851,0.001146216],"category_scores_gemma":[0.003750618,0.00009006036,0.0005054228,0.001490429,0.0002647291,0.0004953091,0.0004699838,0.000453389,0.000726909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003123551,"about_ca_system_score_gemma":0.0003701152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001699337,"about_ca_topic_score_gemma":0.001069267,"domain_scores_codex":[0.9988721,0.0002489674,0.0001489838,0.0002061545,0.0003830008,0.0001408619],"domain_scores_gemma":[0.9984344,0.0006805756,0.0001131496,0.000205479,0.0004987998,0.00006751622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001624664,0.0009344156,0.1143452,0.0004972033,0.0001579885,0.0007141071,0.0006255519,0.02260725,0.07661498,0.00180046,0.003769186,0.776309],"study_design_scores_gemma":[0.00007914183,0.001249743,0.3292378,0.0001690084,0.0001537836,0.001485313,0.002313622,0.5522658,0.08895303,0.005170097,0.01878699,0.0001357673],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.872803,0.0003920964,0.1177478,0.0002084188,0.0001252354,0.000260316,0.00368222,0.0006739292,0.004106969],"genre_scores_gemma":[0.9290572,0.0001331468,0.06375416,0.00003104659,0.00003021239,0.0001853717,0.005432372,0.00002950652,0.001346937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00333555,"threshold_uncertainty_score":0.007717371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1647426410523729,"score_gpt":0.4114857322378034,"score_spread":0.2467430911854305,"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."}}