{"id":"W4289886486","doi":"10.31399/asm.edfa.2007-1.p006","title":"Interconnect Layout Sensitivity and Yield Prediction","year":2007,"lang":"en","type":"article","venue":"EDFA Technical Articles","topic":"Integrated Circuits and Semiconductor Failure Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Abbott (Canada)","funders":"","keywords":"Sensitivity (control systems); Interconnection; Very-large-scale integration; Measure (data warehouse); Computer science; Process (computing); Reliability engineering; Vulnerability (computing); Yield (engineering); Integrated circuit layout; Simple (philosophy); Physical design; Channel (broadcasting); Electronic engineering; Integrated circuit; Circuit design; Engineering; Data mining; Embedded system; Materials science; Telecommunications; 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":[0.0003674772,0.00009492831,0.0001213198,0.00007540207,0.00004231104,0.00002827431,0.00003838863,0.0000949194,0.00005241983],"category_scores_gemma":[0.0000961945,0.00008092194,0.00004581321,0.000172695,0.00004942145,0.0001123548,0.00001724765,0.0001929553,0.00002324164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003128677,"about_ca_system_score_gemma":0.000002477675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004530278,"about_ca_topic_score_gemma":0.0005155432,"domain_scores_codex":[0.9993795,0.00001127052,0.0001825836,0.0001331864,0.00008853491,0.0002049566],"domain_scores_gemma":[0.9996131,0.0001347774,0.00001163391,0.0001328702,0.00002802322,0.00007955969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000003909178,0.00001985893,0.003459194,0.000007967445,0.0000304866,0.00002008642,0.0001260631,0.0001241354,0.9590632,0.001053277,0.001031581,0.03506022],"study_design_scores_gemma":[0.0002495864,0.0001159269,0.04585717,0.00008820045,0.0001104334,0.0001232033,0.0006144249,0.03134542,0.9161639,0.001373864,0.003557714,0.0004001856],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980211,0.000124417,0.0162598,0.0001040503,0.00009200419,0.00005213874,0.00000526028,0.0005285833,0.002622778],"genre_scores_gemma":[0.9994871,0.00001762887,0.0002883495,0.00007131892,0.00009400458,0.000002151105,0.000002351255,0.00001275826,0.00002431629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04289935,"threshold_uncertainty_score":0.3299901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01219957985813986,"score_gpt":0.2014852087334344,"score_spread":0.1892856288752945,"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."}}