{"id":"W2018620666","doi":"10.4028/www.scientific.net/ssp.103-104.301","title":"Resist Stripping for Advanced FEOL Nodes: Improvements to Process Based on Ozone Diffusion by Use of Additives","year":2005,"lang":"en","type":"article","venue":"Diffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena","topic":"Silicon and Solar Cell Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mitel (Canada)","funders":"","keywords":"Resist; Materials science; Stripping (fiber); Diffusion; Ozone; Process (computing); Process engineering; Nanotechnology; Diffusion process; Chemical engineering; Engineering physics; Computer science; Thermodynamics; Composite material; Organic chemistry; Engineering; Innovation diffusion","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":[0.0002152027,0.00033068,0.000230634,0.0003025113,0.0002756957,0.0004714612,0.0005732671,0.0003165072,0.001899301],"category_scores_gemma":[0.0002359589,0.0001467041,0.0002325495,0.0001460163,0.0001839645,0.0006037065,0.0003305146,0.0005088355,0.0007096519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002474942,"about_ca_system_score_gemma":0.0002075759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008349964,"about_ca_topic_score_gemma":0.002411241,"domain_scores_codex":[0.9998564,0.000009203357,0.000006739937,0.00003671879,0.00006562834,0.00002528027],"domain_scores_gemma":[0.9998858,0.00002182134,0.00002696304,0.00001830067,0.00003508556,0.00001212025],"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":[0.0001184947,0.00004999985,0.0005229301,0.0001706273,0.000008053014,0.00007303298,0.00009339848,0.000167045,0.9770229,0.0008250881,0.0002711856,0.02067735],"study_design_scores_gemma":[0.00001659147,0.0002958319,0.001509041,0.00001074661,0.00002142191,0.0002628306,0.0000332576,0.001731643,0.9779897,0.0001046381,0.01800882,0.00001538764],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8907406,0.007416034,0.08777554,0.0004105961,0.0002513464,0.0001882808,0.0002900491,0.001166547,0.01176102],"genre_scores_gemma":[0.9080652,0.003162437,0.07060875,0.0001483039,0.00004254481,0.0000451032,0.0003822058,0.0001567975,0.01738874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001899301,"threshold_uncertainty_score":0.006353796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03459272559132814,"score_gpt":0.2957707457508516,"score_spread":0.2611780201595235,"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."}}