{"id":"W4225328542","doi":"10.36227/techrxiv.19678317.v1","title":"Mitigating re-entrant etch profile undercut in Au etch with an aqua regia variant","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Advancements in Photolithography Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalsa Corporation; Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Undercut; Galvanic cell; Aqua regia; Photoresist; Materials science; Etching (microfabrication); Layer (electronics); Composite material; Metallurgy; Nanotechnology; Optoelectronics; Metal","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000170064,0.0003338289,0.0002059399,0.0001445328,0.0001098367,0.0003812634,0.0003362734,0.0002673046,0.0006443565],"category_scores_gemma":[0.0003004112,0.0002092796,0.000170094,0.0001024452,0.0002089235,0.000251251,0.0002596178,0.0003470674,0.0002400635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000199812,"about_ca_system_score_gemma":0.0001789641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007186603,"about_ca_topic_score_gemma":0.001484412,"domain_scores_codex":[0.9998062,0.00001091721,0.000009206899,0.00004692713,0.00007249215,0.00005434586],"domain_scores_gemma":[0.9998171,0.00002973374,0.00007480024,0.00002512833,0.00004053371,0.00001266302],"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":[0.00001162328,0.000003925018,0.0001115985,0.00003364205,0.000003540403,0.00003946579,0.00002350828,0.00009355626,0.9987796,0.00002733147,0.0000178074,0.0008543848],"study_design_scores_gemma":[0.000001431287,0.00007049529,0.000728537,0.000002000067,0.000005434582,0.0000576207,0.00002024694,0.0006608883,0.9980065,0.000008568793,0.0004359376,0.000002333291],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9955848,0.0005377693,0.002915897,0.0000333557,0.00001586956,0.00001313343,0.00005481549,0.0001386093,0.0007057063],"genre_scores_gemma":[0.9921117,0.0004741869,0.005803859,0.00003692715,0.000005244016,0.00001733637,0.00007182971,0.00005970928,0.001419214],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0007186603,"threshold_uncertainty_score":0.002155602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01796488505703737,"score_gpt":0.2730364448594689,"score_spread":0.2550715598024315,"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."}}