{"id":"W1495084877","doi":"10.22146/ijc.21593","title":"SEPARATION AND IDENTIFICATION OF NORMAL HYDROCARBON, NONADECANE IN THE CABBAGE VEGETABLES SAMPLES (<i>Brassica oleracea VAR. CAPITATA F. ALBA</i>) BY GAS CHROMATOGRAPHY–MASS SPECTROMETRY","year":2010,"lang":"en","type":"article","venue":"Indonesian Journal of Chemistry","topic":"Phytochemicals and Antioxidant Activities","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Atomic Energy (Canada)","funders":"","keywords":"Chemistry; Brassica oleracea; Capitata; Hydrocarbon; Chromatography; Mass spectrometry; Gas chromatography; Brassica; Extraction (chemistry); Gas chromatography–mass spectrometry; Environmental chemistry; Botany; Organic chemistry; Biology","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":[0.0001063676,0.0004696189,0.0001914435,0.001055796,0.0002999333,0.0001585059,0.0001111917,0.0002118407,0.0008770115],"category_scores_gemma":[0.000132577,0.0001052089,0.0001476165,0.000477826,0.0002310691,0.0001234341,0.0001367982,0.000154253,0.0002334524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001753552,"about_ca_system_score_gemma":0.0002467442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002520781,"about_ca_topic_score_gemma":0.005673199,"domain_scores_codex":[0.9999062,0.00001105226,0.000008154051,0.00003096536,0.00003017985,0.00001349825],"domain_scores_gemma":[0.9998865,0.00002714671,0.00002668853,0.000008811205,0.00003668612,0.00001408264],"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":[0.00009278753,0.00001324775,0.002565769,0.00005951567,0.000006898412,0.00008228528,0.00006439371,0.00002358331,0.9953294,0.00001679813,0.00001409982,0.001731307],"study_design_scores_gemma":[0.00001908709,0.0006069368,0.1235704,0.00002910284,0.0000716594,0.00132623,0.0004342155,0.0002759331,0.8702469,0.00009218077,0.003308384,0.00001901851],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961278,0.0008247287,0.001227617,0.00002909773,0.000008888037,0.00002762511,0.00082549,0.0000244811,0.0009042087],"genre_scores_gemma":[0.9879168,0.001493918,0.005064297,0.000057831,0.00001250273,0.00008616515,0.002331518,0.0000204609,0.003016561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002520781,"threshold_uncertainty_score":0.005012274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005593654563118607,"score_gpt":0.2322183880108938,"score_spread":0.2266247334477751,"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."}}