{"id":"W2097473332","doi":"10.1109/ipfa.2011.5992750","title":"Back-side De-processing using CMP for bulk silicon 40-nm graphics processors","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Surface Polishing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advanced Micro Devices (Canada)","funders":"","keywords":"Chemical-mechanical planarization; Process (computing); Computer science; Polishing; Graphics; Die (integrated circuit); Silicon; Materials science; Computer graphics (images); Optoelectronics; Composite material","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":[0.0001251384,0.0005175316,0.0002614738,0.0002824326,0.000253035,0.0004470874,0.0006278657,0.0004018147,0.003126591],"category_scores_gemma":[0.0003140784,0.0002888074,0.0002085947,0.0002409034,0.0001965264,0.0004508568,0.0003362076,0.0007647105,0.001405892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004813188,"about_ca_system_score_gemma":0.0005059767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006732444,"about_ca_topic_score_gemma":0.001519375,"domain_scores_codex":[0.9998018,0.00000932214,0.000005773925,0.00003460894,0.0001268898,0.00002157329],"domain_scores_gemma":[0.999881,0.00002236715,0.00002838366,0.00002199849,0.00003605494,0.00001020266],"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":[0.0000602281,0.0000199512,0.0002200594,0.0001077519,0.000006150946,0.0001153814,0.00003539321,0.0007492665,0.9711879,0.001186326,0.001459471,0.02485205],"study_design_scores_gemma":[0.00002800962,0.0002410321,0.001431277,0.00001377513,0.00001422126,0.0005674158,0.00001725845,0.01010813,0.9640139,0.0003617046,0.02318492,0.00001828448],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4186106,0.003438511,0.529532,0.0008024626,0.0005253522,0.0005345824,0.0007597636,0.004439177,0.04135742],"genre_scores_gemma":[0.6082066,0.001069339,0.3679354,0.0002892792,0.00005663893,0.0002581098,0.0008624237,0.0005010192,0.02082115],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003126591,"threshold_uncertainty_score":0.01045948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05351719257065882,"score_gpt":0.2824972098303321,"score_spread":0.2289800172596732,"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."}}