{"id":"W4247558190","doi":"10.1515/iupac.88.0222","title":"Simultaneous Steam Distillation-Solvent Extraction","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; National Research Council Canada","funders":"","keywords":"Process engineering; Extraction (chemistry); Computer science; Solvent extraction; Distillation; Scale (ratio); Steam distillation; 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":[0.002249071,0.001962774,0.001923663,0.003485944,0.0007896094,0.002124634,0.002243326,0.001331737,0.02727357],"category_scores_gemma":[0.006503518,0.000506003,0.001968994,0.006761836,0.0003813146,0.001349817,0.001955254,0.001575247,0.03294959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001240177,"about_ca_system_score_gemma":0.003173031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01194066,"about_ca_topic_score_gemma":0.02737876,"domain_scores_codex":[0.9975625,0.0004370786,0.0003926233,0.0009312484,0.0004706629,0.0002057859],"domain_scores_gemma":[0.9972425,0.0008151551,0.0004590115,0.00052034,0.0008322634,0.0001308298],"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":[0.00189927,0.0001569413,0.01424258,0.02083146,0.001047654,0.0001676547,0.0001056323,0.001916226,0.003711209,0.002280066,0.8935038,0.0601375],"study_design_scores_gemma":[0.0004950568,0.0001010242,0.01514209,0.001025811,0.0003710932,0.0001509287,0.00007789677,0.0006400289,0.00325532,0.002584958,0.9760854,0.00007053372],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000616384,0.0005321206,0.0004691049,0.00006252225,0.00003120985,0.00005359339,0.9969603,0.000313008,0.0009617004],"genre_scores_gemma":[0.001072101,0.0004600126,0.001406905,0.00006722567,0.000009774168,0.0001759453,0.9960909,0.00005966917,0.0006574688],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02727357,"threshold_uncertainty_score":0.09123915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02399595433453515,"score_gpt":0.4401122553993903,"score_spread":0.4161163010648551,"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."}}