{"id":"W4247959533","doi":"10.1515/iupac.88.0218","title":"Full Evaporation Headspace Analysis","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Hemodynamic Monitoring and Therapy","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; National Research Council Canada","funders":"","keywords":"Computer science; Extraction (chemistry); Process engineering; Sample (material); Evaporation; Sample preparation; Microwave; Chromatography; Chemistry; Engineering","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":[0.002956511,0.002517143,0.002208095,0.002989457,0.001041954,0.002950432,0.003172295,0.001976153,0.0481593],"category_scores_gemma":[0.01005127,0.0005732234,0.002403401,0.003746898,0.0005631823,0.001635968,0.002561296,0.001846688,0.07319577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001217675,"about_ca_system_score_gemma":0.004538848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008045414,"about_ca_topic_score_gemma":0.01646177,"domain_scores_codex":[0.9971836,0.0005020658,0.0004731551,0.000994171,0.0005666893,0.0002803057],"domain_scores_gemma":[0.9958775,0.001023434,0.0005332281,0.001103589,0.001278582,0.0001835889],"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":[0.001096916,0.0001221473,0.006922305,0.008248224,0.0005354775,0.0001384599,0.00006357415,0.0008790934,0.002082885,0.001396857,0.9422572,0.03625679],"study_design_scores_gemma":[0.0004839395,0.00009606921,0.009510985,0.001359143,0.0002658936,0.0002110493,0.00007995132,0.0005785158,0.002664555,0.002934078,0.9817447,0.00007114599],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005688406,0.0006262682,0.0008097911,0.0001102996,0.00007398974,0.0001159987,0.9953703,0.0008414795,0.001482901],"genre_scores_gemma":[0.00126726,0.0004563783,0.001942037,0.0001761446,0.00002736317,0.0004783184,0.9942353,0.0001377983,0.001279386],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0481593,"threshold_uncertainty_score":0.1611089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115992580053156,"score_gpt":0.4730739392295861,"score_spread":0.4519140134290546,"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."}}