{"id":"W4250269073","doi":"10.1515/iupac.88.1417","title":"Thrombocytopenia","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Agricultural safety and regulations","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":[0.001054788,0.0008490745,0.00136666,0.003466423,0.0004397145,0.001962382,0.001048893,0.001028812,0.07216822],"category_scores_gemma":[0.01188735,0.0003579562,0.001240042,0.005184115,0.0002277547,0.001526053,0.001054429,0.001578375,0.02680739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000886417,"about_ca_system_score_gemma":0.00159814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005946749,"about_ca_topic_score_gemma":0.01061388,"domain_scores_codex":[0.9985538,0.0002198613,0.000548772,0.0003278249,0.000242539,0.0001071202],"domain_scores_gemma":[0.994585,0.001909994,0.001327336,0.0009328475,0.001035218,0.0002097019],"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":[0.0006116462,0.00003614687,0.008416674,0.006793441,0.0002032948,0.0001471337,0.00005081091,0.0002634003,0.000237167,0.001432055,0.948844,0.03296424],"study_design_scores_gemma":[0.0006379903,0.00006076988,0.02880205,0.005766022,0.0002556481,0.001001722,0.0001167157,0.0003438334,0.0004109793,0.00380827,0.9587327,0.00006328187],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006890834,0.001296324,0.0002723215,0.0002357263,0.00007787704,0.0001157369,0.9919808,0.0002327901,0.005099398],"genre_scores_gemma":[0.003342032,0.001696639,0.0009567742,0.0006088956,0.0000765096,0.0004665018,0.9904357,0.00007809909,0.002338746],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07216822,"threshold_uncertainty_score":0.2414267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02434972407071015,"score_gpt":0.384873495274601,"score_spread":0.3605237712038908,"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."}}