{"id":"W4236655632","doi":"10.1515/iupac.88.0196","title":"Multiwell Sample Plate","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); Sample (material); Computer science; Scale (ratio); Sample preparation; Process engineering; Microwave; Throughput; Data mining; Chromatography; Engineering; Chemistry; Physics; Telecommunications","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":[0.002490412,0.001841223,0.001999017,0.003531385,0.001058488,0.002908798,0.003370623,0.001592726,0.0866368],"category_scores_gemma":[0.007611886,0.000740222,0.001400478,0.006857189,0.0003843921,0.001402715,0.001883359,0.002270343,0.09583607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00116215,"about_ca_system_score_gemma":0.00306674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007393413,"about_ca_topic_score_gemma":0.01777116,"domain_scores_codex":[0.99685,0.0004653433,0.0004484038,0.001139466,0.0008066582,0.000290193],"domain_scores_gemma":[0.9957319,0.001254705,0.0006098727,0.0009406891,0.00124612,0.0002167052],"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":[0.0006652146,0.000132742,0.004909667,0.004966528,0.0002252362,0.00009168705,0.00006817996,0.0009411362,0.003771854,0.001859643,0.9554718,0.02689624],"study_design_scores_gemma":[0.0002870337,0.00008497999,0.008938799,0.0004129289,0.0001246374,0.0001273868,0.00008589352,0.0004910641,0.003544428,0.002109895,0.9837436,0.00004941937],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004732641,0.0002972244,0.0008763565,0.0000757224,0.00004336693,0.00009089669,0.9958612,0.0007254193,0.001556483],"genre_scores_gemma":[0.0008463883,0.0003123522,0.00210336,0.0001130129,0.00001456985,0.0004807435,0.9945444,0.000129294,0.001455954],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0866368,"threshold_uncertainty_score":0.289829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03570107689994965,"score_gpt":0.4482031047816066,"score_spread":0.412502027881657,"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."}}