{"id":"W4233624090","doi":"10.1515/iupac.73.0618","title":"Squalene","year":2016,"lang":"it","type":"dataset","venue":"IUPAC Standards Online","topic":"Cholesterol and Lipid Metabolism","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan College","funders":"","keywords":"Squalene; Table (database); Chemistry; Food science; Product (mathematics); Commission; Biochemistry; Organic chemistry; Polymer science; Mathematics; Computer science; Political science; Data mining; Law","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":[0.0008299917,0.00233084,0.00156514,0.002984767,0.0009191923,0.002521508,0.002314594,0.001781197,0.05948953],"category_scores_gemma":[0.004976918,0.0005112481,0.002291657,0.003802705,0.0004672441,0.001652562,0.002223453,0.001525838,0.07183271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001267517,"about_ca_system_score_gemma":0.002129857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01717128,"about_ca_topic_score_gemma":0.03728509,"domain_scores_codex":[0.9989725,0.0001733179,0.0001246186,0.0003999038,0.0001944095,0.0001351732],"domain_scores_gemma":[0.9989261,0.0002759617,0.0001617883,0.0002461158,0.000244174,0.0001458574],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008762889,0.0001058301,0.006433158,0.004458716,0.0002852706,0.0001510921,0.00008214414,0.0009015662,0.0009449158,0.002332706,0.9661461,0.01728216],"study_design_scores_gemma":[0.0003855762,0.00007289304,0.008010616,0.0008414903,0.0001546564,0.0001808915,0.0000837415,0.0004413349,0.0007704854,0.002179496,0.9868348,0.00004405828],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006938164,0.0007460613,0.0001490611,0.0001565108,0.00006831525,0.00003686045,0.9956616,0.0004918187,0.001995896],"genre_scores_gemma":[0.001295564,0.0003863775,0.0002894182,0.0001492089,0.00001763004,0.00009479892,0.9964201,0.00006957419,0.001277252],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05948953,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01770704529058393,"score_gpt":0.4074000122896105,"score_spread":0.3896929669990266,"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."}}