{"id":"W2549279743","doi":"10.1177/1687814016671620","title":"Tool wear in disk milling grooving of titanium alloy","year":2016,"lang":"en","type":"article","venue":"Advances in Mechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Materials science; Tool wear; Delamination (geology); Enhanced Data Rates for GSM Evolution; Titanium alloy; Machining; Metallurgy; Scanning electron microscope; Grinding; Alloy; Composite material; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002863407,0.0002436244,0.0003217858,0.0003188079,0.0002874753,0.0002547785,0.000332643,0.0003295113,0.0004178782],"category_scores_gemma":[0.0008608695,0.0001959247,0.0002671663,0.0002307953,0.000264291,0.0002782569,0.0001890864,0.0001802968,0.0000743904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001998543,"about_ca_system_score_gemma":0.00008971133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007921163,"about_ca_topic_score_gemma":0.001405987,"domain_scores_codex":[0.9995762,0.00003870415,0.0000210624,0.00008693084,0.0002134683,0.00006371871],"domain_scores_gemma":[0.9994972,0.0001609255,0.00008595856,0.00007176349,0.0001641726,0.00002006232],"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":[0.0001550843,0.00002453109,0.002835641,0.0001423394,0.00001164355,0.0002294753,0.0002145767,0.0008355013,0.9844692,0.00006126773,0.00006041959,0.01096028],"study_design_scores_gemma":[0.00001858034,0.001263921,0.03479934,0.00001126867,0.00003366169,0.0005328163,0.0001994248,0.009959917,0.9517271,0.0001155038,0.001307028,0.00003136081],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973134,0.0005195403,0.001776865,0.00001130953,0.000008651394,0.00001036763,0.00001964941,0.00002664263,0.0003134675],"genre_scores_gemma":[0.9980791,0.0001274641,0.001252517,0.00001073,0.000002963653,0.00000464161,0.00003438227,0.000007110694,0.0004811417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007921163,"threshold_uncertainty_score":0.001575053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003227160168330154,"score_gpt":0.2049320493769747,"score_spread":0.2017048892086445,"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."}}