{"id":"W4394448047","doi":"10.6084/m9.figshare.21077615","title":"Additional file 1 of Comprehensive chemical profiling of volatile constituents of Angong Niuhuang Pill in vitro and in vivo based on gas chromatography coupled with mass spectrometry","year":2022,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Traditional Chinese Medicine Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Chromatography; Chemistry; Gas chromatography–mass spectrometry; Mass spectrometry; Pill; In vivo; Profiling (computer programming); Pharmacology; Biotechnology; Medicine; Computer science; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001227025,0.0002526431,0.001186448,0.001171711,0.00001725547,0.000005546331,0.0002142526,0.0001094324,0.6627029],"category_scores_gemma":[0.0002536037,0.0002191392,0.0001046508,0.001131141,0.00033281,0.00005431164,0.00007947283,0.0004494978,0.000002647522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008305995,"about_ca_system_score_gemma":0.0004615034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002601473,"about_ca_topic_score_gemma":0.00007278642,"domain_scores_codex":[0.9980264,0.00006282925,0.0006306542,0.0004046743,0.0007115334,0.0001638995],"domain_scores_gemma":[0.9975865,0.00134426,0.0005175599,0.0003319782,0.0001349894,0.00008470818],"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":[0.002125483,0.0007386694,0.0006483719,0.000506844,0.0002577118,0.0002004847,0.00001310216,0.00005968021,0.0273587,3.667297e-7,0.9680673,0.00002326363],"study_design_scores_gemma":[0.06408115,0.007249205,0.05085844,0.04232856,0.004879559,0.0006646984,0.003304638,0.03131349,0.2168519,0.00008832466,0.5748551,0.003524914],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.09708438,0.00002720043,0.000001434774,0.00002326001,0.00001061739,0.0005962061,0.9020016,7.009421e-7,0.0002546359],"genre_scores_gemma":[0.01516213,0.0000051629,0.009010069,0.00004136289,0.00002646114,0.0001371361,0.9755951,0.00001497417,0.000007645029],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6627002,"threshold_uncertainty_score":0.8936237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01667394764357173,"score_gpt":0.2652613962343355,"score_spread":0.2485874485907638,"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."}}