{"id":"W4238646595","doi":"10.1515/iupac.88.0249","title":"Stagewise Contactor","year":2017,"lang":"af","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); Sample (material); Process engineering; Scale (ratio); Sample preparation; Chromatography; Engineering; Chemistry; 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":[0.001896193,0.001907188,0.001387328,0.002556113,0.0009404105,0.003057163,0.002529559,0.001464688,0.1579583],"category_scores_gemma":[0.009542295,0.0007295384,0.002115194,0.004442194,0.0004196053,0.002054666,0.002080477,0.001708769,0.1909337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001182591,"about_ca_system_score_gemma":0.003500259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01204373,"about_ca_topic_score_gemma":0.03277789,"domain_scores_codex":[0.9974807,0.0004119399,0.0003339206,0.0009704502,0.0004855137,0.0003174776],"domain_scores_gemma":[0.9948496,0.001582248,0.000485156,0.001737102,0.001140164,0.0002057156],"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":[0.0005398776,0.00004519727,0.003141945,0.002606957,0.00009714493,0.0000313788,0.0000517343,0.0004406258,0.0009058138,0.001712714,0.9629929,0.02743367],"study_design_scores_gemma":[0.0001655774,0.00003884267,0.003285452,0.0003052393,0.00004547174,0.00004942599,0.0000457036,0.000483491,0.001259461,0.001620158,0.9926792,0.00002192977],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005220496,0.0002595772,0.001216884,0.00009797353,0.00008502579,0.0001273022,0.9894171,0.003522479,0.004751661],"genre_scores_gemma":[0.002082747,0.0003328049,0.00375805,0.0002182646,0.00003148166,0.0004279621,0.9873111,0.0008016603,0.005035797],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1579583,"threshold_uncertainty_score":0.5284232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03430943814177316,"score_gpt":0.4584906983627584,"score_spread":0.4241812602209852,"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."}}