{"id":"W2147833146","doi":"10.1109/test.1988.207865","title":"An algorithmic branch and bound method for PLA test pattern generation","year":2003,"lang":"en","type":"article","venue":"","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Backtracking; Heuristics; Computer science; Branch and bound; Algorithm; Monotonic function; Heuristic; Set (abstract data type); Benchmark (surveying); Test set; Mathematics; Artificial intelligence; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004077175,0.0000745994,0.00007843556,0.000036289,0.0001666897,0.0002572585,0.0001458202,0.00003175905,0.000006125114],"category_scores_gemma":[0.0000870362,0.00006658067,0.00001762368,0.00009092485,0.000009113101,0.0003475578,0.00001263596,0.00003726672,0.000002940934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008911008,"about_ca_system_score_gemma":0.0000282394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003843434,"about_ca_topic_score_gemma":0.00004250785,"domain_scores_codex":[0.9993225,0.00004426663,0.0001223078,0.0002766424,0.00007335044,0.0001609715],"domain_scores_gemma":[0.9995051,0.0001686693,0.00003309687,0.0001848841,0.000044513,0.00006375126],"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":[6.591487e-9,0.00002565845,0.002692364,0.000005848444,0.000002566563,0.000001315403,0.0001464433,0.00004315695,0.03083214,0.003502789,0.000124832,0.9626229],"study_design_scores_gemma":[0.0002648953,0.0001129442,0.00129056,0.000004127849,0.000003850496,0.00004345547,0.00001098813,0.9815712,0.01364312,0.002152389,0.0007555497,0.0001469339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01525897,0.00004536035,0.98369,0.0001146423,0.0001007422,0.000109757,0.000001855958,0.00008168268,0.0005970486],"genre_scores_gemma":[0.8113196,0.000001886739,0.1877806,0.0006249905,0.0001192323,0.00001352154,0.00000294979,0.000005984382,0.0001311813],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.981528,"threshold_uncertainty_score":0.2715081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0335414820340071,"score_gpt":0.2963730149451067,"score_spread":0.2628315329110996,"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."}}