{"id":"W4236295288","doi":"10.1515/iupac.88.0187","title":"Fluorous 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":"Extraction (chemistry); Computer science; Process engineering; Sample (material); Sample preparation; Scale (ratio); Chromatography; Chemistry; Engineering; 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":[0.002360411,0.002448295,0.002093992,0.004526268,0.001090594,0.00257354,0.00274829,0.002161166,0.04443954],"category_scores_gemma":[0.009761441,0.0006226844,0.001881352,0.00662309,0.0004647113,0.001818118,0.002079667,0.002086347,0.05906682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00179771,"about_ca_system_score_gemma":0.003901901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01394073,"about_ca_topic_score_gemma":0.02523334,"domain_scores_codex":[0.9974791,0.0004182425,0.0003427417,0.0009492806,0.0005601124,0.0002505917],"domain_scores_gemma":[0.9964949,0.001133395,0.0005115864,0.0007100008,0.001005333,0.0001446658],"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":[0.0005473354,0.00006844104,0.005396754,0.01103477,0.0003428837,0.0001013172,0.00006158346,0.001041357,0.001777401,0.001992258,0.9437257,0.03391024],"study_design_scores_gemma":[0.0001942602,0.00003431533,0.005125588,0.001174483,0.0001363525,0.000107031,0.00005213004,0.0003226302,0.001417974,0.002172415,0.9892244,0.00003842223],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002902088,0.0005675616,0.0004907901,0.00008486961,0.00003461343,0.00003879671,0.996721,0.0004460756,0.001325987],"genre_scores_gemma":[0.0005660511,0.0004727354,0.001155501,0.0001054094,0.000008874891,0.000146719,0.996713,0.00007378345,0.0007579082],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04443954,"threshold_uncertainty_score":0.148665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03061046017115645,"score_gpt":0.4627958345516454,"score_spread":0.4321853743804889,"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."}}