{"id":"W4251093801","doi":"10.1503/cmaj.1040280","title":"Correction","year":2004,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Electrolyte and hormonal disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Information retrieval; Data science; World Wide Web","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004492348,0.00005851605,0.0001141118,0.0001332545,0.000162344,0.00002894206,0.00005152015,0.0002171418,0.001973585],"category_scores_gemma":[0.0009521873,0.00005278478,0.00007947491,0.0001696213,0.00001376179,0.00006249051,0.00000235221,0.0007709566,0.0003316332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001325381,"about_ca_system_score_gemma":0.004320145,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002670436,"about_ca_topic_score_gemma":0.02662003,"domain_scores_codex":[0.9986256,0.00002146797,0.0001805429,0.00007171987,0.0007967382,0.0003039371],"domain_scores_gemma":[0.9984032,0.0000279446,0.00006218007,0.00004107096,0.0002106786,0.001254953],"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":[0.00004759246,0.0001162073,0.04459606,0.000007291215,0.0002526923,0.001383745,0.0003505653,0.00002666973,0.0004498617,0.001530968,0.7723735,0.1788649],"study_design_scores_gemma":[0.003133956,0.0003064725,0.3291115,0.0001058809,0.00006049723,0.003668457,0.0002707846,0.0001089671,0.0001664481,0.001495789,0.6614241,0.0001471872],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5141857,0.0007250403,0.000610367,0.2648096,0.002410824,0.0001879299,0.00000389068,0.0000659502,0.2170006],"genre_scores_gemma":[0.9673491,0.0002377383,0.00005365656,0.02824562,0.001387087,0.000001993187,0.000007442637,0.00001092437,0.0027065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4531633,"threshold_uncertainty_score":0.9989387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004281647438322811,"score_gpt":0.2259322804821613,"score_spread":0.2216506330438385,"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."}}