{"id":"W2054890061","doi":"10.2307/3316000","title":"Optimal sampling for repeated binary measurements","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sequence (biology); Sampling (signal processing); Markov chain; Binary number; Pseudorandom binary sequence; Mathematics; Term (time); Dirichlet distribution; Nonparametric statistics; Computer science; Mathematical optimization; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.0005913757,0.00009117419,0.000161932,0.0001760431,0.0001454,0.0001127921,0.0004253655,0.00004504179,0.00000614803],"category_scores_gemma":[0.0002602804,0.00008593419,0.00005062639,0.0001385179,0.00003386825,0.0001738847,0.000010572,0.0001281883,0.000001715388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001835949,"about_ca_system_score_gemma":0.001726411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003547458,"about_ca_topic_score_gemma":0.0007665801,"domain_scores_codex":[0.9990996,0.00003035771,0.0003145022,0.0001179148,0.0001568665,0.0002808219],"domain_scores_gemma":[0.9986312,0.00006080807,0.0001805963,0.0001639843,0.0004536791,0.0005097326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004944529,0.00007130813,0.0004879809,0.0001067908,0.00024906,0.001115376,0.00346608,0.0268892,0.002830194,0.6833349,0.01823339,0.2631662],"study_design_scores_gemma":[0.007054297,0.002772025,0.005138481,0.0007250934,0.0002335468,0.00171347,0.000121514,0.02697719,0.005524652,0.9097058,0.0386376,0.001396369],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001249935,0.0002224739,0.9971797,0.0004625137,0.0006086009,0.00008388349,0.0000675532,0.000005754542,0.000119564],"genre_scores_gemma":[0.05515504,0.000005879137,0.9444555,0.0002445045,0.00009287504,0.000001151941,0.000002499648,0.000009650998,0.00003292231],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2617699,"threshold_uncertainty_score":0.3504294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09253567411219904,"score_gpt":0.2995387924183253,"score_spread":0.2070031183061262,"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."}}