{"id":"W2127195807","doi":"10.1093/biostatistics/4.3.479","title":"Conditional analysis of mixed Poisson processes with baseline counts: implications for trial design and analysis","year":2003,"lang":"en","type":"article","venue":"Biostatistics","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Statistics; Baseline (sea); Sample size determination; Count data; Negative binomial distribution; Multiple baseline design; Poisson distribution; Randomization; Mathematics; Computer science; Econometrics; Clinical trial; Medicine; 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":[0.2938994,0.00246885,0.006307442,0.002812228,0.001167921,0.003870376,0.0046299,0.004473187,0.006798404],"category_scores_gemma":[0.5427244,0.001603299,0.003779893,0.005212967,0.006473278,0.006693748,0.004822844,0.007478864,0.001040492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003162824,"about_ca_system_score_gemma":0.008692903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001482081,"about_ca_topic_score_gemma":0.001309727,"domain_scores_codex":[0.6834062,0.29106,0.006421868,0.006117291,0.01180984,0.001184651],"domain_scores_gemma":[0.3671664,0.5912948,0.01701962,0.01702096,0.006122682,0.001375657],"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":[0.001955068,0.0002857527,0.005016419,0.001971176,0.001608476,0.0004837158,0.0006846879,0.05369543,0.0007804954,0.7823526,0.007104655,0.1440614],"study_design_scores_gemma":[0.0008398354,0.000729365,0.001403923,0.0004065403,0.0003893303,0.0002492455,0.00006389323,0.1992466,0.0007316846,0.7892795,0.006565856,0.00009419143],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001732124,0.001132686,0.9938918,0.001573943,0.0001596742,0.0007718524,0.000110938,0.0001321556,0.0004949088],"genre_scores_gemma":[0.05637375,0.002376362,0.9283614,0.001814113,0.0004317468,0.009374337,0.0002594306,0.0001309258,0.0008778929],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2938994,"threshold_uncertainty_score":0.8707478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4690235198847609,"score_gpt":0.5372107865117601,"score_spread":0.06818726662699925,"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."}}