{"id":"W2164135279","doi":"10.1145/2206781.2206827","title":"Lazy suspect-set computation","year":2012,"lang":"en","type":"article","venue":"","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Toronto","funders":"","keywords":"Debugging; Computer science; Suspect; Automatic test pattern generation; Iddq testing; Test set; Set (abstract data type); Test vector; Fault detection and isolation; Computation; Software bug; Chip; Computer engineering; Algorithm; Reliability engineering; Embedded system; Software; Artificial intelligence; Programming language; Electronic circuit; Engineering; Electronic engineering; CMOS","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":[0.002622525,0.001258854,0.002008376,0.002746925,0.001681599,0.002803623,0.004120731,0.00169889,0.009130641],"category_scores_gemma":[0.01499962,0.000811526,0.002099555,0.002351843,0.002488068,0.00548629,0.003930569,0.002107789,0.001615297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001542823,"about_ca_system_score_gemma":0.002869544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003499675,"about_ca_topic_score_gemma":0.007324269,"domain_scores_codex":[0.997484,0.0005031744,0.0002501383,0.0006055705,0.0007434514,0.0004136956],"domain_scores_gemma":[0.9896215,0.00572162,0.0005701372,0.002881589,0.0009230151,0.0002821455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002534959,0.0005276689,0.009524656,0.001056418,0.00034776,0.0007735664,0.0008424392,0.343084,0.01760722,0.1449746,0.02453274,0.4541939],"study_design_scores_gemma":[0.0001494713,0.0001234964,0.0004102146,0.00003933092,0.0001090167,0.0001739632,0.00009472539,0.7946233,0.006813789,0.1944707,0.002954458,0.00003762788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07356736,0.0005244126,0.9096346,0.001053171,0.0001453936,0.0002849392,0.0008686794,0.008533479,0.005387892],"genre_scores_gemma":[0.4787522,0.0002012633,0.5117861,0.0004538999,0.0001674149,0.0003693865,0.002273921,0.0008348508,0.005160977],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009130641,"threshold_uncertainty_score":0.030545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04205799625704049,"score_gpt":0.2771312005130238,"score_spread":0.2350732042559833,"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."}}