{"id":"W4400300787","doi":"10.53555/sfs.v10i3.2842","title":"Profiling of Bioactive Constituents of Sargassum wightii Greville ex J. Agardh by GC-MS Analysis","year":2023,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"Phytochemistry and Biological Activities","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sargassum; Gas chromatography–mass spectrometry; Profiling (computer programming); Chromatography; Chemistry; Botany; Biology; Mass spectrometry; Computer science; Algae","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":[0.002096853,0.0001158065,0.0005108542,0.00006592268,0.00009215352,0.00003285352,0.000458372,0.00008095867,0.000161178],"category_scores_gemma":[0.000542359,0.00004232511,0.000182218,0.002650365,0.0009782378,0.0003125058,0.00007781238,0.0001267707,9.115398e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001782972,"about_ca_system_score_gemma":0.00003397596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005226184,"about_ca_topic_score_gemma":0.0004785436,"domain_scores_codex":[0.998364,0.0002481332,0.0005696127,0.0001821197,0.0004080275,0.0002281523],"domain_scores_gemma":[0.9982008,0.0008485915,0.0006524354,0.00003678564,0.0002015535,0.00005988715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006180082,0.00008530949,0.7545756,0.000007844244,0.0000568286,0.000002452534,0.00003574049,0.00002546765,0.2434966,0.000004760484,0.0005698602,0.001077753],"study_design_scores_gemma":[0.0001079026,0.0004800608,0.8408918,0.00004178779,0.00002769655,0.000002952879,0.000955179,0.00001613506,0.1565595,0.0001907042,0.0006126509,0.0001137043],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980357,0.0001418879,0.000001919947,0.0002721426,0.0001217174,0.00005846768,0.0002180253,0.000006731409,0.001143384],"genre_scores_gemma":[0.9995124,0.0002309215,0.00008028177,0.00001587376,0.00005178688,0.000001269289,0.00002318259,3.439774e-7,0.00008389946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08693709,"threshold_uncertainty_score":0.3604358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1486014070901679,"score_gpt":0.268577491995781,"score_spread":0.119976084905613,"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."}}