{"id":"W2032569847","doi":"10.1016/j.wear.2013.11.003","title":"Surface evolution models for abrasive slurry jet micro-machining of channels and holes in glass","year":2013,"lang":"en","type":"article","venue":"Wear","topic":"Erosion and Abrasive Machining","field":"Environmental Science","cited_by":79,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; University of Toronto; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Borosilicate glass; Materials science; Slurry; Abrasive; Machining; Brittleness; Jet (fluid); Composite material; Erosion; Metallurgy; Mechanics","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":[0.0004690858,0.0006341853,0.0008601402,0.00061898,0.0005868014,0.0009427668,0.001854566,0.002182267,0.002082462],"category_scores_gemma":[0.001510972,0.0007177872,0.001141171,0.000428216,0.001085195,0.0008619016,0.000578006,0.0007958508,0.000226252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001658907,"about_ca_system_score_gemma":0.0007137967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03069245,"about_ca_topic_score_gemma":0.01727308,"domain_scores_codex":[0.9998455,0.00003308732,0.000007923194,0.00003226474,0.00003777058,0.00004351004],"domain_scores_gemma":[0.9993004,0.0004065618,0.00008891537,0.00003930693,0.00009920191,0.00006560737],"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":[0.00002920223,0.00002949876,0.0009569054,0.00002650493,0.00001313904,0.00007558953,0.00007226119,0.987784,0.002189903,0.006610167,0.0001704637,0.002042393],"study_design_scores_gemma":[0.000004101468,0.000004244158,0.0002290515,0.000001392527,0.000002167334,0.00000940651,0.00000883852,0.9988731,0.0001151127,0.0006873086,0.00006204953,0.000003253079],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6854377,0.001974173,0.2914975,0.0008950126,0.0001391137,0.0001505917,0.000357154,0.000351273,0.0191974],"genre_scores_gemma":[0.9847537,0.0002982665,0.006119242,0.00004466475,0.00002012439,0.00004580333,0.00008937521,0.00006809138,0.008560796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03069245,"threshold_uncertainty_score":0.06102765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01543994133866825,"score_gpt":0.2359223397664189,"score_spread":0.2204823984277506,"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."}}