{"id":"W1484361789","doi":"10.1109/iscas.1994.409197","title":"Pseudo-random vector compaction for sequential testability","year":2002,"lang":"en","type":"article","venue":"","topic":"VLSI and Analog Circuit Testing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Testability; Benchmark (surveying); Set (abstract data type); Algorithm; Random testing; Computer science; Fault (geology); Compaction; Vector (molecular biology); Mathematics; Engineering; Statistics; Biology; Test case; Machine learning","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":[0.0002069478,0.0000800673,0.0001112109,0.00003417214,0.000154008,0.0001176564,0.0002717241,0.00003085648,0.0001222544],"category_scores_gemma":[0.0001419527,0.00006887779,0.00007809398,0.0001626129,0.00002209352,0.0003451262,0.00003293907,0.00005648205,0.00005762041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004305888,"about_ca_system_score_gemma":0.00001242925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004772242,"about_ca_topic_score_gemma":0.00001460707,"domain_scores_codex":[0.9992331,0.00002883701,0.0001525364,0.0002539143,0.0001174614,0.0002142016],"domain_scores_gemma":[0.9993285,0.0002292698,0.00004263211,0.0002619221,0.00006895396,0.00006870001],"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":[0.00000410337,0.0007490478,0.01872282,0.0001413489,0.0000663333,0.00001390639,0.001575478,0.0005734023,0.05885356,0.07657988,0.01956481,0.8231553],"study_design_scores_gemma":[0.001105375,0.0001032899,0.003933048,0.000009578434,0.000007868553,0.00002666996,0.00001406918,0.986401,0.003299409,0.002942245,0.001950613,0.0002068028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0276797,0.00002452449,0.9631379,0.0006266729,0.000322736,0.0001838815,0.000002036779,0.0003363609,0.007686242],"genre_scores_gemma":[0.9911557,0.000001132333,0.008163218,0.000166732,0.0001327207,0.0000123125,0.000001229553,0.00000428016,0.0003626832],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9858276,"threshold_uncertainty_score":0.2808755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06216036711787259,"score_gpt":0.2634782913471381,"score_spread":0.2013179242292655,"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."}}