{"id":"W2584073294","doi":"10.1016/b978-1-78548-096-6.50002-x","title":"Plasma Etching in Microelectronics","year":2017,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Plasma Diagnostics and Applications","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Microelectronics; Lithography; Multiple patterning; Trimming; Plasma etching; Etching (microfabrication); Materials science; Reactive-ion etching; Semiconductor industry; Dry etching; Transistor; Plasma; Nanotechnology; Next-generation lithography; Optoelectronics; Semiconductor; Extreme ultraviolet lithography; Electron-beam lithography; Resist; Engineering; Electrical engineering; Mechanical engineering; Manufacturing engineering; Physics; Layer (electronics)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007661619,0.0002984597,0.0003227739,0.0001223874,0.00008216844,0.00007359267,0.0003576793,0.0002825433,0.00002084855],"category_scores_gemma":[0.00001252426,0.0003401149,0.00009703934,0.000003529627,0.00003929687,0.00002529998,0.00005833749,0.0006949232,0.0003231062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001305383,"about_ca_system_score_gemma":0.00005033661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.511889e-7,"about_ca_topic_score_gemma":0.0002347773,"domain_scores_codex":[0.9990904,0.000002836237,0.0002662046,0.0002338243,0.0001087352,0.000298003],"domain_scores_gemma":[0.9992304,0.00007091312,0.00007399081,0.0005357733,0.00001833073,0.00007052849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[9.804636e-7,0.000002817423,0.000001733099,0.00005088839,0.00003925009,0.00002538846,0.00006052851,0.0003060198,0.000162723,0.01785715,0.0003157475,0.9811768],"study_design_scores_gemma":[0.0001507348,0.000006942221,0.000006491959,0.0002786661,0.00002765254,0.000007855442,6.932954e-7,0.001471141,0.0005604649,0.01646295,0.9806788,0.0003476072],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001519569,0.0005425042,0.000005615639,0.00003427588,0.0002022226,0.0002735672,0.0000588352,0.0001158845,0.9972475],"genre_scores_gemma":[0.02186767,0.0008498901,0.0004751674,0.00004044129,0.0002009186,0.00007269595,0.00004738088,0.0001556577,0.9762902],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9808292,"threshold_uncertainty_score":0.9999051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009634836411950757,"score_gpt":0.2132734046540285,"score_spread":0.2036385682420777,"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."}}