{"id":"W4251494555","doi":"10.1515/iupac.88.0332","title":"Porous Membrane","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; Sample (material); Process engineering; Throughput; Scale (ratio); Biochemical engineering; 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":[0.001781007,0.001848983,0.00160795,0.003911788,0.0008335801,0.002458953,0.002533967,0.001584259,0.05893756],"category_scores_gemma":[0.008421964,0.0005679814,0.001781296,0.007691108,0.0003499016,0.001480725,0.001921893,0.001522912,0.06426462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001430689,"about_ca_system_score_gemma":0.004010897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01225295,"about_ca_topic_score_gemma":0.02368167,"domain_scores_codex":[0.9976419,0.000409051,0.0003370623,0.0008644102,0.0005076062,0.0002400162],"domain_scores_gemma":[0.9969066,0.001121189,0.0005907745,0.0005444858,0.000667936,0.0001690897],"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":[0.0007726681,0.00007846192,0.005220705,0.01236293,0.0004045367,0.00009251776,0.0000593406,0.001075583,0.001309924,0.002311366,0.9383734,0.03793857],"study_design_scores_gemma":[0.0002893668,0.00005443048,0.00649314,0.001007302,0.0001707443,0.0001150765,0.00004959204,0.0003959477,0.001056909,0.002152434,0.9881802,0.00003488677],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000277239,0.000410506,0.0003078435,0.00005821701,0.00002048718,0.00004008397,0.9975173,0.000331387,0.001036786],"genre_scores_gemma":[0.0007043309,0.0004411568,0.0009641073,0.00008148977,0.000008156648,0.0001851706,0.9968174,0.00007099501,0.0007272756],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05893756,"threshold_uncertainty_score":0.1971657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02750750003706899,"score_gpt":0.4345892971254732,"score_spread":0.4070817970884042,"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."}}