{"id":"W1964954201","doi":"10.1016/j.jmatprotec.2015.04.007","title":"Implementation of a shadow mask for direct writing in abrasive jet micro-machining","year":2015,"lang":"en","type":"article","venue":"Journal of Materials Processing Technology","topic":"Erosion and Abrasive Machining","field":"Environmental Science","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick; University of Toronto; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Shadow mask; Jet (fluid); Materials science; Shadow (psychology); Optics; Perpendicular; Nozzle; Abrasive; Machining; Surface micromachining; Mechanical engineering; Composite material; Geometry; Engineering; Physics; Mechanics; Fabrication","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001319411,0.0001120084,0.0003446455,0.0002471556,0.00005403615,0.00003565313,0.0002574022,0.00009731603,0.00008623736],"category_scores_gemma":[0.0002772884,0.00009404433,0.00003512174,0.0002425842,0.0001031173,0.0002510256,0.0001272031,0.0001156121,0.000003028883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001058767,"about_ca_system_score_gemma":0.00005384224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006133747,"about_ca_topic_score_gemma":0.00005090761,"domain_scores_codex":[0.9986811,0.00005653079,0.0007331907,0.0001428319,0.0001724467,0.0002139475],"domain_scores_gemma":[0.9988692,0.00004709653,0.0009085718,0.00007588582,0.00005602942,0.00004315993],"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":[0.00007139269,0.00003705512,0.1152356,0.00004381242,0.000005555084,0.00001104743,0.0008121294,0.00005216227,0.8597987,0.00005137929,0.0001186876,0.02376251],"study_design_scores_gemma":[0.001532826,0.0003446997,0.009200798,0.0002702175,0.0000188101,0.0001218158,0.004980863,0.00005000259,0.979599,0.003586364,0.0001663053,0.0001283249],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977626,0.0001259942,0.001022461,0.0005997512,0.0001372316,0.0001305695,0.0000078826,0.00002086539,0.0001926042],"genre_scores_gemma":[0.9762976,0.000008872726,0.0235535,0.00007079566,0.00003761558,0.000009134515,0.000001832447,0.00001490663,0.000005793446],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1198003,"threshold_uncertainty_score":0.3835016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02186277273469241,"score_gpt":0.3225200029070365,"score_spread":0.3006572301723441,"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."}}