{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000155069,0.0004906349,0.0003724312,0.0002794829,0.0005969199,0.0004794878,0.0004612001,0.0005064925,0.03719849],"category_scores_gemma":[0.0002215725,0.0001680793,0.0002725407,0.0002126088,0.0001813797,0.0009930559,0.000473383,0.0004198137,0.007218322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00055157,"about_ca_system_score_gemma":0.0005940311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001819357,"about_ca_topic_score_gemma":0.005426715,"domain_scores_codex":[0.9999143,0.000005539913,0.000003898262,0.00001641237,0.00003706078,0.00002275102],"domain_scores_gemma":[0.9999365,0.000008926386,0.000005303062,0.0000138949,0.00002407703,0.00001135263],"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":[0.0007730562,0.00007719869,0.0007947242,0.002042774,0.00005106743,0.0006035136,0.0002164178,0.001658662,0.7891299,0.04653707,0.08618244,0.07193319],"study_design_scores_gemma":[0.00008917688,0.0006834772,0.002189865,0.0004322233,0.00006668824,0.000488934,0.0003039144,0.002833118,0.3803905,0.01218802,0.6003005,0.00003351585],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3860775,0.05035076,0.01369435,0.00849473,0.005693785,0.000459829,0.01028094,0.003013019,0.5219352],"genre_scores_gemma":[0.7218844,0.02104273,0.01287563,0.0007663243,0.0003795415,0.0002759841,0.004662841,0.0004860531,0.2376265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03719849,"threshold_uncertainty_score":0.1244413,"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."}}