{"id":"W2319505397","doi":"10.1149/1.2911520","title":"Silicides for 22nm and Beyond","year":2008,"lang":"en","type":"article","venue":"ECS Transactions","topic":"Semiconductor materials and interfaces","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"Basic Energy Sciences; Office of Science; U.S. Department of Energy","keywords":"Silicide; Materials science; Architecture; Engineering physics; Scaling; CMOS; Nanotechnology; Stability (learning theory); Computer architecture; Computer science; Optoelectronics; Electronic engineering; Silicon; Engineering; Mathematics; Geography","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":[0.0001965581,0.0004328656,0.0002182641,0.0002428007,0.0006382671,0.0008277703,0.0003277202,0.0006433761,0.01120115],"category_scores_gemma":[0.000284168,0.0001837467,0.0001719659,0.0001733506,0.0003392939,0.001308283,0.0007083531,0.0006740312,0.003919663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006908051,"about_ca_system_score_gemma":0.0006948684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006983395,"about_ca_topic_score_gemma":0.002111354,"domain_scores_codex":[0.9999121,0.00000763755,0.000006850344,0.00001781838,0.00003874109,0.00001685897],"domain_scores_gemma":[0.9999131,0.00001380407,0.00001188858,0.0000139356,0.00003055629,0.00001677471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001951527,0.00005823245,0.00106425,0.001541483,0.00002475358,0.001155455,0.0008326825,0.001697034,0.263643,0.3676867,0.07706951,0.2850318],"study_design_scores_gemma":[0.000006876892,0.00007668044,0.0003773914,0.0001504924,0.000008588126,0.0004364858,0.0001027551,0.0005664318,0.01938527,0.02308982,0.9557866,0.00001263388],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1095621,0.3164798,0.02907492,0.02531727,0.007704394,0.0001817639,0.001066273,0.001752657,0.5088608],"genre_scores_gemma":[0.454891,0.1620835,0.06464431,0.004743068,0.001949694,0.0002790441,0.001017045,0.0004875288,0.3099048],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01120115,"threshold_uncertainty_score":0.03747153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01997811239362756,"score_gpt":0.2426225828818715,"score_spread":0.222644470488244,"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."}}