{"id":"W4231728853","doi":"10.1515/iupac.88.0212","title":"Cryogenic Trap","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Radioactive element chemistry and processing","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; National Research Council Canada","funders":"","keywords":"Trap (plumbing); Computer science; Extraction (chemistry); Sample (material); Process engineering; 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":[0.001792694,0.001986712,0.001599251,0.002906885,0.001186774,0.00236257,0.003560863,0.001668056,0.05524564],"category_scores_gemma":[0.006438792,0.0006820763,0.001524311,0.004818059,0.0004687995,0.001700144,0.002405409,0.00202095,0.0797456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001530916,"about_ca_system_score_gemma":0.003175166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01493646,"about_ca_topic_score_gemma":0.03123899,"domain_scores_codex":[0.9985928,0.0002564396,0.0001555775,0.0005141702,0.0003025666,0.0001784239],"domain_scores_gemma":[0.9974846,0.000666665,0.00036091,0.0006375932,0.0006884007,0.0001619086],"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":[0.0004757447,0.00004234127,0.003825435,0.004101081,0.0001919473,0.00006989556,0.00006411922,0.0008595453,0.001276608,0.00189839,0.9731843,0.01401072],"study_design_scores_gemma":[0.0002046539,0.00003618604,0.005516964,0.0005687379,0.00008739155,0.00009295625,0.00006851387,0.0003686144,0.001042493,0.002001108,0.9899797,0.00003268803],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002861739,0.0002834502,0.0003515246,0.00006914258,0.00002914285,0.00002299353,0.9972555,0.0005739579,0.001128185],"genre_scores_gemma":[0.0005578318,0.0002534461,0.0007625188,0.0000775475,0.000009025352,0.0001146138,0.9973959,0.0001150808,0.0007139954],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05524564,"threshold_uncertainty_score":0.184815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02127581320937769,"score_gpt":0.422664438281369,"score_spread":0.4013886250719913,"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."}}