{"id":"W617994174","doi":"","title":"Development of a metabolic syndrome personal health record system.","year":2015,"lang":"en","type":"article","venue":"PubMed","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metabolic syndrome; Promotion (chess); Medicine; Health promotion; Quarter (Canadian coin); Population; Diabetes mellitus; Family medicine; Gerontology; Environmental health; Public health; Nursing; Geography; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003572054,0.000159724,0.0005694192,0.0001730358,0.0004461818,0.000004730307,0.0002366709,0.0001572325,0.00005753716],"category_scores_gemma":[0.0004291905,0.0001432137,0.00005762748,0.0003621615,0.00005309974,0.0001012326,0.0001186338,0.0004221757,0.0004947312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006807801,"about_ca_system_score_gemma":0.00228238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002964588,"about_ca_topic_score_gemma":0.002501077,"domain_scores_codex":[0.9961995,0.0006614343,0.001343657,0.000302966,0.0005119853,0.0009804721],"domain_scores_gemma":[0.9978099,0.0001959739,0.0005683206,0.0002818666,0.0003953533,0.0007486214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001995172,0.0001572972,0.2626768,0.003101015,0.0001226031,0.00002291671,0.08649964,0.000003307671,0.000003784126,0.01222371,0.007284401,0.627705],"study_design_scores_gemma":[0.0006377028,0.0000891233,0.5149457,0.0006782729,0.00002947716,0.00003864266,0.1358311,0.0004848031,0.0001478458,0.0003345614,0.3462665,0.000516288],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836023,0.001739789,0.0003645152,0.002065199,0.002782728,0.00333721,0.00002837717,0.0001928465,0.00588698],"genre_scores_gemma":[0.9906279,0.00001754714,0.003285184,0.0005288433,0.0001946915,0.004129471,0.00001076808,0.00003007315,0.001175491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6271887,"threshold_uncertainty_score":0.6358933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3344712874987728,"score_gpt":0.4370041318925105,"score_spread":0.1025328443937377,"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."}}