{"id":"W2092379463","doi":"10.1007/s11746-000-0146-x","title":"Predicting oxidative stability of vegetable oils using neural network system and endogenous oil components","year":2000,"lang":"en","type":"article","venue":"Journal of the American Oil Chemists Society","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Vegetable oil; Predictability; Composition (language); Food science; Chemistry; Tocopherol; Artificial neural network; Chemical composition; Antioxidant; Biochemistry; Organic chemistry; Vitamin E; Mathematics; Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001437747,0.0001754405,0.0004819566,0.000007687959,0.00009999197,0.00001369069,0.000319575,0.00006235501,0.00000409958],"category_scores_gemma":[0.00005869479,0.0001340614,0.0002214157,0.0002765173,0.0004516138,0.0001047155,0.00007453409,0.0004700002,1.499555e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003482619,"about_ca_system_score_gemma":0.00001066561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003474457,"about_ca_topic_score_gemma":3.957904e-7,"domain_scores_codex":[0.9988073,0.00003064117,0.0004679981,0.0001261395,0.0002623737,0.000305568],"domain_scores_gemma":[0.9989519,0.0001510545,0.0004882784,0.0002507095,0.00008682128,0.00007125774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002362622,0.00001780201,0.004001961,0.000277573,0.000126821,0.000002511691,0.0003921894,0.06123566,0.9286911,4.52633e-7,0.00001527191,0.005215039],"study_design_scores_gemma":[0.0003307098,0.0000269966,0.0004147357,0.0002561394,0.00007979139,0.0002377553,0.001361746,0.03632082,0.9607434,0.00001543199,0.00005497726,0.0001574808],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983389,0.0009241666,0.00003309042,0.00002491394,0.00006503637,0.00001858046,0.000009105039,0.00009069512,0.0004954751],"genre_scores_gemma":[0.994077,0.0004055761,0.00535304,0.00001670483,0.0001120969,0.000001049289,3.763586e-7,0.00002482745,0.000009293602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03205233,"threshold_uncertainty_score":0.5466866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01888969750734714,"score_gpt":0.2135819831834254,"score_spread":0.1946922856760782,"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."}}