{"id":"W1968058010","doi":"10.1088/0960-1317/18/6/065016","title":"Characterization and modeling of 2D-glass micro-machining by spark-assisted chemical engraving (SACE) with constant velocity","year":2008,"lang":"en","type":"article","venue":"Journal of Micromechanics and Microengineering","topic":"Advanced Machining and Optimization Techniques","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Engraving; Machining; SPARK (programming language); Materials science; Electrical discharge machining; Characterization (materials science); Isotropic etching; Etching (microfabrication); Constant (computer programming); Mechanical engineering; Dry etching; Composite material; Nanotechnology; Metallurgy; Engineering; Computer science","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":[0.0002466729,0.0003916749,0.0004535083,0.0002646546,0.0001921102,0.0005989813,0.0006739689,0.001056483,0.0008291146],"category_scores_gemma":[0.0005362503,0.0004035364,0.0004479871,0.0002528794,0.0004173351,0.0004098932,0.0001737297,0.0002349776,0.0001818263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005315201,"about_ca_system_score_gemma":0.0008225173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006277914,"about_ca_topic_score_gemma":0.005614965,"domain_scores_codex":[0.9998152,0.00001528249,0.000007175583,0.00003635824,0.0001024685,0.00002359587],"domain_scores_gemma":[0.9997323,0.0001205723,0.00004847218,0.00003994539,0.00004683845,0.00001184994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000055788,0.00004303848,0.001620112,0.00009258233,0.00001477446,0.0001290056,0.0001047072,0.9104786,0.0806952,0.001178059,0.0002182812,0.005369861],"study_design_scores_gemma":[0.000004020584,0.00002034045,0.0006497852,0.00000148669,0.000002312373,0.00001591172,0.000007058707,0.9919241,0.00708421,0.00006811246,0.0002173991,0.000005215735],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7958488,0.0004430374,0.1935759,0.0001891616,0.00003203527,0.0001367156,0.0008297787,0.0009807585,0.007963829],"genre_scores_gemma":[0.9795633,0.0001862772,0.01857271,0.00001242665,0.000003102319,0.00007276428,0.0002130748,0.00003289359,0.001343418],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006277914,"threshold_uncertainty_score":0.01248276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007383871026519924,"score_gpt":0.1881492718337782,"score_spread":0.1807654008072583,"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."}}