{"id":"W28424106","doi":"10.1017/s0954579417000505","title":"Methods and Sample Size Effect Evaluation for Wafer Level Statistical Bin Limits Determination with Poisson Distributions","year":2004,"lang":"en","type":"article","venue":"IE interfaces","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Canadian Institutes of Health Research","keywords":"Bin; Percentile; Poisson distribution; Statistics; Sample size determination; Transformation (genetics); Mathematics; Standard deviation; Monte Carlo method; Statistical model; Normal distribution; Exponential distribution; Computer science; Algorithm","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0007694605,0.0001314,0.0001699486,0.00005564637,0.00009627071,0.00007720648,0.00003722113,0.0001034068,0.00002099842],"category_scores_gemma":[0.001400977,0.0001028496,0.00002383564,0.0001036432,0.000025754,0.0001335858,0.000007326765,0.00007685028,0.000004922941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001590108,"about_ca_system_score_gemma":0.00001968543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001187373,"about_ca_topic_score_gemma":0.0001022067,"domain_scores_codex":[0.9992267,0.0001070578,0.0001961911,0.0001678642,0.0001499021,0.0001522321],"domain_scores_gemma":[0.998108,0.001605598,0.00003841774,0.00009324797,0.0001062113,0.00004855965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002623772,0.00003598948,0.0001547888,0.0001592318,0.00008512992,0.000001217263,0.0004048552,0.008277179,0.07110176,0.0003537616,0.0002322115,0.9189315],"study_design_scores_gemma":[0.004071385,0.001781119,0.00732343,0.0002553742,0.0002016105,0.0000328824,0.000122234,0.07055198,0.9088934,0.004501072,0.001861109,0.0004043725],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4399136,0.00004850807,0.5590876,0.00002619106,0.0002527905,0.0004255567,0.0001401634,0.00006515328,0.00004043904],"genre_scores_gemma":[0.9567261,0.000002701671,0.04298171,0.000003327961,0.00007284475,0.0001608757,0.00002161594,0.00001813775,0.00001264044],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9185271,"threshold_uncertainty_score":0.4194085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05734522576882654,"score_gpt":0.3752386324511694,"score_spread":0.3178934066823428,"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."}}