{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006053713,0.0002192522,0.0005000607,0.0001540679,0.00007388699,0.00006598219,0.0002648162,0.0001740106,0.00003507167],"category_scores_gemma":[0.0001402706,0.0001727965,0.0001561002,0.0003489628,0.0003044161,0.0003159822,0.0000221877,0.0005625373,6.215123e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002717232,"about_ca_system_score_gemma":0.0001508303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005715789,"about_ca_topic_score_gemma":0.00000845839,"domain_scores_codex":[0.9981287,0.00004430965,0.0008226919,0.0002094177,0.0005292256,0.0002657256],"domain_scores_gemma":[0.9984587,0.0002000622,0.0007563914,0.0003030824,0.0001417792,0.0001399167],"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":[0.0001107482,0.0002324342,0.009978468,0.0002506425,0.00007793247,0.00004145313,0.0003356478,0.000001299975,0.9881424,0.00003915277,0.0005869666,0.0002028479],"study_design_scores_gemma":[0.001192211,0.00007307078,0.04597248,0.000200924,0.0001225727,0.0009320547,0.000223964,0.00005618295,0.9502857,0.0003726471,0.0004083596,0.0001597834],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955913,0.002181004,0.0002360448,0.0008408062,0.00007325684,0.000130885,0.00003703324,0.000009278619,0.0009003993],"genre_scores_gemma":[0.9987799,0.0003544108,0.0003946588,0.0000346993,0.00031871,0.000007310526,0.0000379769,0.00002099536,0.00005133477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03785666,"threshold_uncertainty_score":0.7046437,"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."}}