{"id":"W2959812924","doi":"10.2337/cd19-0025","title":"The Diabetes Code: Prevent and Reverse Type 2 Diabetes Naturally","year":2019,"lang":"en","type":"article","venue":"Clinical Diabetes","topic":"Diet and metabolism studies","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Type 2 diabetes; Medicine; Diabetes mellitus; Type 1 diabetes; Family medicine; Endocrinology","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":[0.001202026,0.0002516052,0.0007575715,0.00003883896,0.0001673919,0.00005963421,0.0001935964,0.0001774781,0.0000851102],"category_scores_gemma":[0.002495389,0.0001483112,0.0002322504,0.0001875795,0.0004652287,0.0001035333,0.000254989,0.0004651917,0.0003363696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001341234,"about_ca_system_score_gemma":0.00006132893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.663685e-7,"about_ca_topic_score_gemma":0.0000023947,"domain_scores_codex":[0.9979159,0.0001475248,0.0006027995,0.0004555639,0.0002745577,0.0006036091],"domain_scores_gemma":[0.9967803,0.002088457,0.0001583908,0.000532297,0.000202842,0.0002376919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003307982,0.0001457512,0.9434541,0.0001364373,0.0003515179,0.000001049849,0.00005038735,1.483661e-7,0.001565116,0.0003897931,0.0267421,0.02713053],"study_design_scores_gemma":[0.001016335,0.000609973,0.7438027,0.000192564,0.0002838651,9.473426e-8,0.00007209714,0.0001075903,0.0006800368,0.0008745851,0.2521553,0.0002048723],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9696795,0.02009428,5.277694e-8,0.004450954,0.002379322,0.0005799272,0.00001076486,0.0000870313,0.002718158],"genre_scores_gemma":[0.9827789,0.004940935,0.0001861887,0.003752211,0.0005450254,0.00003141105,0.00001686783,0.00003707549,0.007711364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2254132,"threshold_uncertainty_score":0.6047955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02482255961819237,"score_gpt":0.3298892976395617,"score_spread":0.3050667380213694,"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."}}