{"id":"W4256036435","doi":"10.1515/iupac.88.0328","title":"Perfusate","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; National Research Council Canada","funders":"","keywords":"Computer science; Extraction (chemistry); Sample (material); Throughput; Process engineering; 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":[0.001658709,0.002577466,0.001805698,0.003709177,0.0008235011,0.002333678,0.002560225,0.002379208,0.04883908],"category_scores_gemma":[0.008819404,0.0005695577,0.001926824,0.005269631,0.0004034752,0.001603217,0.002272328,0.002011306,0.07339108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001633199,"about_ca_system_score_gemma":0.003140012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01381067,"about_ca_topic_score_gemma":0.02200259,"domain_scores_codex":[0.9978119,0.0003345039,0.0003786441,0.0007238931,0.0004997115,0.0002512882],"domain_scores_gemma":[0.9964945,0.0008906297,0.0006585135,0.0006769773,0.001074159,0.0002053091],"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":[0.001064839,0.000136332,0.008378109,0.007468491,0.0003016207,0.0001032022,0.00004850769,0.0007770992,0.001238115,0.001230111,0.9432806,0.0359729],"study_design_scores_gemma":[0.0003947676,0.0001089447,0.01268379,0.001716753,0.000202566,0.0002451719,0.00009213063,0.0007079213,0.001397864,0.002047058,0.9803405,0.00006253604],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004520133,0.0004662345,0.0002248954,0.000101168,0.00004100233,0.00004286951,0.9974089,0.0002912817,0.0009716662],"genre_scores_gemma":[0.0006774247,0.0003084586,0.0005822422,0.0001171081,0.00001485413,0.0001328221,0.9976078,0.00004166173,0.00051754],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04883908,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0248697573274195,"score_gpt":0.4652362287003621,"score_spread":0.4403664713729426,"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."}}