{"id":"W3204914590","doi":"","title":"EXPLORING POTENTIAL OF COCONUT MEAT AS A FUNCTIONAL FOOD","year":2019,"lang":"en","type":"article","venue":"Advanced Food and Nutritional Sciences","topic":"Coconut Research and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coconut oil; Food science; Lauric acid; Fatty acid; Biology; Chemistry; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006919243,0.00007494075,0.00009921248,0.00005453737,0.0001852487,0.00002715753,0.0001256039,0.00002415155,0.0006822954],"category_scores_gemma":[0.00002405112,0.00006672693,0.00004964662,0.0001848716,0.0002384707,0.0003649656,0.00005302633,0.00007873821,0.00001575182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001049082,"about_ca_system_score_gemma":0.0000678835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005863948,"about_ca_topic_score_gemma":0.000006681981,"domain_scores_codex":[0.9990301,0.000005707393,0.0001321539,0.0002571049,0.0003874248,0.0001875657],"domain_scores_gemma":[0.9995967,0.0001078213,0.0000454408,0.00008514853,0.00007715241,0.0000876994],"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":[0.0001115792,0.0001609663,0.001954661,0.0001258499,0.00003174295,7.062486e-7,0.00003243813,0.0001326878,0.8725026,0.1157584,0.0000507726,0.009137513],"study_design_scores_gemma":[0.00368796,0.001713107,0.01375789,0.0003094952,0.0000199629,0.00008468948,0.003680773,0.0003030653,0.8026394,0.1555931,0.0177095,0.0005011287],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906885,0.0006112692,0.00006616434,0.0004969686,0.00003771067,0.0000904226,0.00007112866,0.00002138099,0.007916476],"genre_scores_gemma":[0.9986158,0.0002644291,0.0007233511,0.00002428649,0.00008346896,0.00009456199,0.0000220512,0.000003454388,0.0001685967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06986327,"threshold_uncertainty_score":0.7470656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06317927124385832,"score_gpt":0.2790035806194685,"score_spread":0.2158243093756102,"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."}}