{"id":"W7095721938","doi":"","title":"Reliability Analysis Combining Multiple Inspection Techniques","year":2006,"lang":"en","type":"article","venue":"","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reliability (semiconductor); Probabilistic logic; Sample (material); Statistical power; Statistical analysis; Sample size determination; Probability distribution","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":[],"consensus_categories":[],"category_scores_codex":[0.007744331,0.001987129,0.002266658,0.005051605,0.00051745,0.001616922,0.001614594,0.001251302,0.001627746],"category_scores_gemma":[0.02720316,0.0008489767,0.002626426,0.002521385,0.0009350882,0.002360039,0.001593681,0.001653255,0.0006630835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00107056,"about_ca_system_score_gemma":0.00119735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001593127,"about_ca_topic_score_gemma":0.001321201,"domain_scores_codex":[0.9886329,0.002723569,0.0004613271,0.001142718,0.00655602,0.000483554],"domain_scores_gemma":[0.9768531,0.01176743,0.002487834,0.003226232,0.005443291,0.0002220399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003869338,0.0002044892,0.01559885,0.000736426,0.001035953,0.0006119039,0.0002726656,0.5564129,0.02157858,0.01635242,0.001896807,0.384912],"study_design_scores_gemma":[0.00002744553,0.000646371,0.00907859,0.0001092221,0.0004480095,0.00066553,0.0000906206,0.9586033,0.009140964,0.01828054,0.002800029,0.0001093538],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02958701,0.001159346,0.9652008,0.0001617634,0.00007854438,0.0001343266,0.00007947182,0.0006759171,0.002922643],"genre_scores_gemma":[0.640788,0.00150913,0.3532663,0.0001251143,0.0003334373,0.0003388452,0.0002983792,0.000247579,0.003093202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007744331,"threshold_uncertainty_score":0.04095638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008421667012556398,"score_gpt":0.2213008465799457,"score_spread":0.2128791795673893,"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."}}