{"id":"W1986710173","doi":"10.1016/s0197-2456(03)00103-x","title":"The role of the data coordinating center in the DIG trial","year":2003,"lang":"en","type":"article","venue":"Controlled Clinical Trials","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hamilton General Hospital","funders":"National Heart, Lung, and Blood Institute; U.S. Department of Veterans Affairs","keywords":"Dig; Digitalis; Veterans Affairs; Heart failure; Clinical trial; Ejection fraction; Medicine; Randomized controlled trial; Center (category theory); Computer science; Internal medicine; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","open_science","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.8218087,0.0002250815,0.00767228,0.0000637835,0.0002949193,0.0008777658,0.00795273,0.0001367164,0.001247069],"category_scores_gemma":[0.9099538,0.00005190164,0.004981642,0.0009682482,0.0002171936,0.0001177899,0.0003349023,0.0004087939,0.0002322198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008414458,"about_ca_system_score_gemma":0.000168134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004773774,"about_ca_topic_score_gemma":0.00005301754,"domain_scores_codex":[0.3614126,0.56157,0.06581039,0.001760807,0.008814535,0.000631588],"domain_scores_gemma":[0.06830904,0.8769309,0.03254947,0.02087133,0.001174369,0.0001649004],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.03631732,0.002491845,0.1127642,0.00002279282,0.004389674,0.000005825455,0.0008634268,0.00007019078,0.00008015377,0.1665064,0.1655064,0.5109817],"study_design_scores_gemma":[0.1347126,0.0001576565,0.00174711,0.00004362096,0.0009279419,0.000002080978,0.00195732,0.005158864,0.000007322159,0.07457503,0.780561,0.0001493653],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4233523,0.03518717,0.00577041,0.05070077,0.02689788,0.07646672,0.0004924345,0.00002363087,0.3811087],"genre_scores_gemma":[0.9950178,0.00008537534,0.0001156646,0.0006246433,0.0005057977,0.0001417337,0.000002070807,0.000007202224,0.003499661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6150547,"threshold_uncertainty_score":0.9996659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9441819685772945,"score_gpt":0.6842715447334784,"score_spread":0.2599104238438161,"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."}}