{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001733386,0.0001613912,0.0001585302,0.0002038814,0.0002069455,0.0003343229,0.0002402392,0.0003668003,0.0009106164],"category_scores_gemma":[0.0003949316,0.0002396275,0.0002152337,0.0001439117,0.0006401977,0.0003546924,0.0001864923,0.0003352028,0.0001324076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002447001,"about_ca_system_score_gemma":0.0002392343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001036678,"about_ca_topic_score_gemma":0.001855464,"domain_scores_codex":[0.99986,0.00001704823,0.000003923841,0.00002176917,0.00005572323,0.00004142034],"domain_scores_gemma":[0.9998513,0.00008171006,0.00002878226,0.0000141938,0.00001140418,0.00001257134],"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":[0.000289673,0.00003902177,0.0006255373,0.0001306995,0.000009176887,0.0004381977,0.0001963135,0.00465473,0.970894,0.006003432,0.0001739143,0.01654529],"study_design_scores_gemma":[0.00003418748,0.0003444975,0.00792515,0.00001396417,0.0000114372,0.0005209643,0.0001296751,0.007809302,0.9763324,0.001427049,0.005428482,0.00002284721],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9671041,0.007645324,0.01637375,0.0001615292,0.0001131462,0.00002671297,0.00003072516,0.00009001016,0.008454588],"genre_scores_gemma":[0.9936897,0.0008069482,0.002666982,0.00001622302,0.0000131637,0.000004712756,0.00001462531,0.00000777214,0.002779862],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001036678,"threshold_uncertainty_score":0.003046274,"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."}}