{"id":"W4236460383","doi":"10.1515/iupac.88.0299","title":"Coated Vessel Format","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":"Computer science; Extraction (chemistry); Sample (material); Throughput; Scale (ratio); Process engineering; Microwave; Sample preparation; Chromatography; Chemistry; Engineering; Telecommunications; 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":[0.002258021,0.002144205,0.001820297,0.004419941,0.001047397,0.003670517,0.003954825,0.001946602,0.1590104],"category_scores_gemma":[0.01111257,0.0007861303,0.001684675,0.008372678,0.0004484212,0.002275987,0.002518015,0.001944874,0.2019359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001477075,"about_ca_system_score_gemma":0.003295926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01134038,"about_ca_topic_score_gemma":0.02041108,"domain_scores_codex":[0.9969709,0.0005181638,0.0004626854,0.001082976,0.000665903,0.0002993525],"domain_scores_gemma":[0.9948164,0.001539797,0.0008326881,0.001120721,0.00141128,0.000279211],"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":[0.0004578791,0.00005231825,0.00186648,0.003640322,0.0001395128,0.00005023715,0.00004303963,0.0004586553,0.000972251,0.001464154,0.9745148,0.01634039],"study_design_scores_gemma":[0.0001820533,0.00003896736,0.003131241,0.0003591981,0.00007026175,0.00005660862,0.00004514657,0.0001952724,0.001012406,0.001505519,0.993375,0.00002837372],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001998683,0.0001652805,0.0003735022,0.0000585885,0.00003304907,0.00005532593,0.9965995,0.0007325694,0.001782331],"genre_scores_gemma":[0.0004258603,0.000210264,0.0009835839,0.00009452878,0.00001291687,0.0002014096,0.9965301,0.0001852387,0.001356112],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1590104,"threshold_uncertainty_score":0.5319427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02933027641384588,"score_gpt":0.4382119931751294,"score_spread":0.4088817167612835,"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."}}