{"id":"W2795572471","doi":"10.1016/j.precisioneng.2018.03.010","title":"Abrasive jet turning of glass and PMMA rods and the micro-machining of helical channels","year":2018,"lang":"en","type":"article","venue":"Precision Engineering","topic":"Erosion and Abrasive Machining","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Rod; Materials science; Machining; Abrasive; Surface micromachining; Jet (fluid); Composite material; Microfluidics; Brittleness; Mold; Particle (ecology); Mechanical engineering; Nanotechnology; Mechanics; Metallurgy; Fabrication; Engineering","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":[0.0005505072,0.0001152281,0.0002036478,0.00004308127,0.00007773538,0.00001810936,0.0001363557,0.00004389586,0.0001126642],"category_scores_gemma":[0.0003751637,0.00007691827,0.00003493332,0.0001240169,0.0002523528,0.0001140846,0.0003448407,0.0001334624,0.000005657895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000102129,"about_ca_system_score_gemma":0.000002125974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003793796,"about_ca_topic_score_gemma":0.000002970602,"domain_scores_codex":[0.9992006,0.0000416603,0.0002332075,0.0001933275,0.0001817385,0.0001494244],"domain_scores_gemma":[0.9992695,0.0004295353,0.00008857699,0.0001368035,0.00001182001,0.00006375107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001202601,0.00002416586,0.05439631,0.00004186565,0.00002322512,0.000001781295,0.006496333,0.009285107,0.8993011,0.0007731354,0.00005831575,0.02947845],"study_design_scores_gemma":[0.00252368,0.0002703848,0.2249946,0.0005154812,0.00003983983,0.00005437266,0.0004663523,0.4056918,0.3631227,0.0003929588,0.001531446,0.000396311],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853748,0.0002178735,0.01341018,0.00007954561,0.0001280927,0.0001035981,0.000002318285,0.00001743594,0.0006661499],"genre_scores_gemma":[0.995581,0.00004955332,0.004250306,0.00003813452,0.00004177535,0.000003727536,5.649991e-7,0.00001206285,0.00002284491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5361783,"threshold_uncertainty_score":0.3136636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006481941423723534,"score_gpt":0.2233311793927186,"score_spread":0.216849237968995,"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."}}