{"id":"W4249086106","doi":"10.1515/iupac.88.0830","title":"Fundus","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Retinal and Optic Conditions","field":"Medicine","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; Data mining; 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":[0.0008962605,0.001353394,0.001232227,0.003744051,0.0007821531,0.003189726,0.002021879,0.001854069,0.2204012],"category_scores_gemma":[0.01068146,0.0004557317,0.001339962,0.005256744,0.0003273779,0.002371464,0.002247397,0.001332352,0.2135487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001567965,"about_ca_system_score_gemma":0.002426917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01678845,"about_ca_topic_score_gemma":0.02902215,"domain_scores_codex":[0.9987881,0.0001906059,0.0002459328,0.0004007175,0.0002209691,0.0001536952],"domain_scores_gemma":[0.9963602,0.000877377,0.0005294574,0.0007104348,0.001274588,0.0002478194],"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":[0.0001060337,0.00001024167,0.00142591,0.001408893,0.00003056624,0.0000313883,0.00002173619,0.00008321423,0.00006476195,0.0007497345,0.9871292,0.008938327],"study_design_scores_gemma":[0.0001184621,0.00001513274,0.003983156,0.00109853,0.00003640821,0.0001366831,0.00007574161,0.0001232194,0.0001507866,0.001606023,0.9926336,0.00002222622],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001453497,0.0002757173,0.0001079339,0.0001719081,0.00006713261,0.00003106424,0.9950193,0.0003961094,0.003785429],"genre_scores_gemma":[0.0007796306,0.0003709759,0.000446124,0.0003542842,0.00003925698,0.0001292548,0.9944506,0.0001120662,0.003317833],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2204012,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02746637295571935,"score_gpt":0.4699621032921943,"score_spread":0.4424957303364749,"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."}}