{"id":"W4246569346","doi":"10.1515/iupac.88.0999","title":"Lymph","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Hematological disorders and diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Computer science; Linguistics; Philosophy","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":[0.001547616,0.001413635,0.001470631,0.003841569,0.0008445015,0.004148735,0.002311389,0.001914218,0.2546684],"category_scores_gemma":[0.01433421,0.0006359654,0.001603743,0.006036898,0.0003680796,0.002894526,0.002627808,0.001581011,0.2626569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001644453,"about_ca_system_score_gemma":0.00301809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0104839,"about_ca_topic_score_gemma":0.01814916,"domain_scores_codex":[0.9976527,0.0004222243,0.0005389422,0.0007251058,0.0004097117,0.0002512503],"domain_scores_gemma":[0.9943191,0.0016214,0.0006962658,0.001313525,0.00167641,0.0003732836],"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":[0.0001503822,0.00001448066,0.001399424,0.002182377,0.0000439555,0.0000282435,0.000034725,0.0001019141,0.0001138873,0.001226306,0.9844509,0.01025333],"study_design_scores_gemma":[0.0001229899,0.00001350631,0.002069097,0.001014409,0.00002803736,0.00006734819,0.00005555852,0.00009039118,0.0001453813,0.001325044,0.9950506,0.00001767964],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001006737,0.0002031635,0.000132674,0.0001420787,0.00006207226,0.00003727357,0.9958181,0.0003939402,0.003110026],"genre_scores_gemma":[0.0004579453,0.0002602189,0.0004168295,0.0003208084,0.00002894093,0.000156388,0.995805,0.0001442856,0.002409625],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2546684,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02716282557288043,"score_gpt":0.4604289981478772,"score_spread":0.4332661725749968,"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."}}