{"id":"W2080813654","doi":"10.1002/sim.1173","title":"Number needed to treat (NNT): estimation of a measure of clinical benefit","year":2001,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; McMaster University Medical Centre","funders":"","keywords":"Number needed to treat; Estimator; Context (archaeology); Event (particle physics); Medicine; Randomized controlled trial; Statistics; Absolute risk reduction; Clinical trial; Confidence interval; Econometrics; Computer science; Relative risk; Mathematics; Surgery; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1480948,0.002585815,0.01363843,0.004387716,0.0008595958,0.003356621,0.003636725,0.006760537,0.005711677],"category_scores_gemma":[0.370938,0.0006415002,0.00615368,0.003518105,0.004594005,0.005935766,0.003131372,0.008134321,0.001209748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004130373,"about_ca_system_score_gemma":0.004161833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001183021,"about_ca_topic_score_gemma":0.0008052694,"domain_scores_codex":[0.7831093,0.1750394,0.01253703,0.008525112,0.02014905,0.0006400527],"domain_scores_gemma":[0.6751333,0.302113,0.01092495,0.006502638,0.004221972,0.001104255],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.01245565,0.0009632795,0.02074474,0.04512102,0.0570669,0.0006736637,0.001060552,0.07617289,0.001739971,0.1594189,0.05730305,0.5672793],"study_design_scores_gemma":[0.00478714,0.01190939,0.01097438,0.01463574,0.02676404,0.00172453,0.0006366548,0.1250965,0.004483172,0.6531008,0.145196,0.0006918387],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.017492,0.1557528,0.761569,0.01721848,0.01540074,0.01323605,0.006309848,0.001089063,0.01193203],"genre_scores_gemma":[0.3659635,0.04870826,0.4981882,0.01937308,0.006594221,0.05207067,0.003702559,0.0006521079,0.004747273],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8519052,"threshold_uncertainty_score":0.7832097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5337564789862494,"score_gpt":0.6268482031556304,"score_spread":0.09309172416938094,"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."}}