{"id":"W2151137402","doi":"10.1093/jnci/dju317","title":"How Best to Determine the Mortality Benefit From Screening Mammography: Dueling Results and Methodologies From Canada","year":2014,"lang":"en","type":"letter","venue":"JNCI Journal of the National Cancer Institute","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Mammography; Mammography screening; Medicine; Demography; Sociology; Breast cancer; Cancer; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0214085,0.0004575294,0.001327188,0.001535415,0.003412683,0.003087608,0.002032009,0.00484592,0.003781374],"category_scores_gemma":[0.1104617,0.0005172959,0.001137088,0.002724656,0.001756397,0.0009638494,0.0009864015,0.006971962,0.0008445941],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02866393,"about_ca_system_score_gemma":0.05322661,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9276214,"about_ca_topic_score_gemma":0.9667014,"domain_scores_codex":[0.9901917,0.004060832,0.001405114,0.0004524305,0.002940167,0.0009497316],"domain_scores_gemma":[0.9048441,0.04514135,0.0021827,0.001852261,0.04265516,0.003324533],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009335694,0.0001119196,0.1420328,0.0006814547,0.0004726679,0.0009781157,0.002364747,0.000710962,0.0003738109,0.005195043,0.6734777,0.1726672],"study_design_scores_gemma":[0.001166099,0.0003263309,0.2048087,0.006003527,0.002201169,0.002480545,0.01144169,0.00570232,0.002151382,0.01881547,0.7445023,0.000400527],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.02065894,0.00885995,0.001352231,0.9455695,0.003589961,0.0001509982,0.002395936,0.00004862019,0.01737392],"genre_scores_gemma":[0.2569608,0.01522044,0.01482702,0.6865453,0.006944151,0.0003811327,0.001674419,0.0002649801,0.01718172],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9785915,"threshold_uncertainty_score":0.2079723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.315200509960043,"score_gpt":0.3960791977577702,"score_spread":0.08087868779772728,"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."}}