{"id":"W2915452479","doi":"10.1149/ma2008-01/16/673","title":"Silicides for 32nm and Beyond","year":2008,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Semiconductor materials and interfaces","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Psychology; Geology","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":[0.0001098554,0.00009592524,0.0001243108,0.00001825109,0.0001446184,0.00003888881,0.0000572897,0.00002391382,0.0001021959],"category_scores_gemma":[0.00002353522,0.00008622006,0.00003234771,0.0000179915,0.00004174216,0.00008937415,0.00002037125,0.00004368007,0.00001671635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003873527,"about_ca_system_score_gemma":0.00001459581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001959628,"about_ca_topic_score_gemma":8.77568e-7,"domain_scores_codex":[0.9994479,0.000007939132,0.0001703227,0.0001526756,0.00005153657,0.0001695547],"domain_scores_gemma":[0.9996523,0.00009689399,0.00008554228,0.00008172063,0.00003254807,0.00005095313],"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":[0.00001589398,0.0000460629,0.01750562,0.00002054043,0.00003221569,0.000001192065,0.0006471673,0.0002789595,0.9762964,0.0001828566,0.004444927,0.0005281408],"study_design_scores_gemma":[0.0002848601,0.00004217879,0.01264947,0.00002645384,0.00001029171,0.000003629948,0.0003137409,0.00004851146,0.9772872,0.001696306,0.00748895,0.0001483455],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9182597,0.00009462184,0.000003049603,0.0000645816,0.0002188899,0.00009105621,0.00002034775,0.00002391039,0.08122389],"genre_scores_gemma":[0.9982958,0.000002778181,0.0008457032,0.00004762624,0.0003968844,0.00001204295,0.00001079929,0.00001409488,0.0003742124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08084968,"threshold_uncertainty_score":0.3515952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02244987709033742,"score_gpt":0.25169657538388,"score_spread":0.2292466982935426,"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."}}