{"id":"W3205365085","doi":"10.15353/cjds.v10i2.795","title":"Diabetes, Art, and Data Resonance","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Disability Studies","topic":"Dietary Effects on Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interpretability; Centrality; Data collection; Legibility; Diabetes management; Value (mathematics); Tracking (education); Psychology; Data science; Computer science; Medicine; Cognitive psychology; Diabetes mellitus; Sociology; Artificial intelligence; Type 2 diabetes; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007861674,0.00009627156,0.0004510247,0.00003507271,0.0001038803,0.00001696018,0.0001184987,0.00003111805,0.00004626894],"category_scores_gemma":[0.004199191,0.00007921257,0.00004319704,0.0001422953,0.0005555569,0.000129129,0.00005827734,0.0002159048,0.000005250276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002522754,"about_ca_system_score_gemma":0.001143479,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003509354,"about_ca_topic_score_gemma":0.06170263,"domain_scores_codex":[0.9989498,0.000102343,0.0003260997,0.0002098406,0.0001465411,0.0002653205],"domain_scores_gemma":[0.9981543,0.000314057,0.0000812576,0.0005500777,0.0002626411,0.0006376457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001731921,0.00004288878,0.9159811,0.0004101539,0.0001859704,0.000301129,0.000326522,3.72467e-7,0.00001765635,0.00006475363,0.05135376,0.03129836],"study_design_scores_gemma":[0.0006019329,0.000303315,0.8170521,0.000422662,0.0001592733,0.0001765066,0.001475096,0.0000195482,0.0000592077,0.0003580168,0.1792815,0.00009083005],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8693023,0.09675418,9.918165e-7,0.03267223,0.0003581891,0.0001183711,0.00008632435,0.000004097525,0.0007033299],"genre_scores_gemma":[0.9956602,0.001396434,0.00082041,0.001611129,0.0002256819,0.000001257634,0.00001335732,0.000009700343,0.0002618301],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1279277,"threshold_uncertainty_score":0.9554188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0845347320978754,"score_gpt":0.3606347455151008,"score_spread":0.2761000134172253,"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."}}