{"id":"W4242607930","doi":"10.1515/iupac.88.0238","title":"Differential Contactor","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":"Contactor; Computer science; Extraction (chemistry); Process engineering; Sample (material); Sample preparation; Microwave; Chromatography; Chemistry; Engineering; Physics; Power (physics)","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":[0.001819443,0.0023566,0.0016976,0.003902368,0.001048252,0.002706071,0.003092469,0.001863042,0.07421526],"category_scores_gemma":[0.01006099,0.0006196883,0.001860491,0.006684529,0.0004296967,0.002082133,0.002300013,0.001746015,0.09426497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001449205,"about_ca_system_score_gemma":0.003254863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01476484,"about_ca_topic_score_gemma":0.03255187,"domain_scores_codex":[0.9971615,0.0004773633,0.0003708286,0.001047873,0.0006450323,0.0002974703],"domain_scores_gemma":[0.996093,0.001362052,0.0004853337,0.0009098611,0.0009884882,0.0001612519],"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":[0.0007108339,0.00007153609,0.005320325,0.005994049,0.0002093205,0.0000742222,0.00006001796,0.000907764,0.0010444,0.00226334,0.949304,0.03404022],"study_design_scores_gemma":[0.000229292,0.00004872145,0.005140638,0.0007346799,0.0001014638,0.0001050111,0.00006682023,0.0007012234,0.001377986,0.002663904,0.9887926,0.00003765322],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004314922,0.0004905018,0.0007347168,0.00007871482,0.00004974031,0.00006057966,0.9948173,0.001193584,0.002143385],"genre_scores_gemma":[0.001302298,0.0004428106,0.001801652,0.0001516529,0.00001706949,0.0002362975,0.9942083,0.0002019195,0.001638012],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07421526,"threshold_uncertainty_score":0.2482748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.028771282825437,"score_gpt":0.4396490492858829,"score_spread":0.4108777664604459,"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."}}