{"id":"W2109495827","doi":"10.1109/tsm.2007.907613","title":"A Fab-Wide APC Sampling Application","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Semiconductor Manufacturing","topic":"Integrated Circuits and Semiconductor Failure Analysis","field":"Engineering","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Metrology; Reliability engineering; Sampling (signal processing); Event (particle physics); Process (computing); Computer science; Process variation; Duration (music); Fault detection and isolation; Engineering; Semiconductor device fabrication; Microprocessor; Manufacturing engineering; Real-time computing; Embedded system; Wafer; Artificial intelligence; Operating system; Detector; Mathematics; Telecommunications","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":[],"consensus_categories":[],"category_scores_codex":[0.0003965412,0.0005455496,0.0004268051,0.000651163,0.0003904367,0.000678603,0.0006881646,0.0005113247,0.01012713],"category_scores_gemma":[0.001053119,0.0001940303,0.0001776382,0.0006588179,0.000144737,0.000322533,0.0005741729,0.0004037999,0.002882939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004998087,"about_ca_system_score_gemma":0.0006615294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002960004,"about_ca_topic_score_gemma":0.003162276,"domain_scores_codex":[0.9994319,0.00003560119,0.00001616803,0.0001489873,0.0003266794,0.00004055985],"domain_scores_gemma":[0.9994393,0.0001267722,0.00003447676,0.000125131,0.0002197385,0.00005460985],"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":[0.001339069,0.0003392192,0.01063035,0.0001921933,0.0000401041,0.001214982,0.0003661641,0.01556645,0.2120005,0.003353009,0.04742302,0.707535],"study_design_scores_gemma":[0.0002432903,0.0009160828,0.01734358,0.00003368989,0.00005077179,0.002985696,0.0002136268,0.5737139,0.2664023,0.003299905,0.1347167,0.00008043417],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1956087,0.0003840665,0.6626334,0.0006491314,0.0002204283,0.0008549161,0.00323216,0.09267763,0.04373959],"genre_scores_gemma":[0.7209039,0.0001673201,0.2475569,0.0004211172,0.0000780161,0.0002318259,0.002709372,0.001029218,0.02690235],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01012713,"threshold_uncertainty_score":0.03387862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01603917981644576,"score_gpt":0.2311549802360548,"score_spread":0.215115800419609,"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."}}