{"id":"W2131455420","doi":"10.1115/1.1535190","title":"Drilling in Bone: Modeling Heat Generation and Temperature Distribution","year":2003,"lang":"en","type":"article","venue":"Journal of Biomechanical Engineering","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":230,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Drill; Drilling; Heat generation; Heat transfer; Thermal; Materials science; Machining; Finite element method; Mechanics; Parametric statistics; Mechanical engineering; Composite material; Structural engineering; Engineering; Metallurgy; Thermodynamics; Physics","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":[0.0002189472,0.0003923037,0.0003799456,0.0003094554,0.0002678896,0.0004816779,0.0007097833,0.001002376,0.0009843525],"category_scores_gemma":[0.0007977864,0.0004669998,0.0005346179,0.0003163865,0.0004896837,0.0005574089,0.0003914133,0.0004311633,0.0002016853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003972353,"about_ca_system_score_gemma":0.0006786456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007967118,"about_ca_topic_score_gemma":0.005648311,"domain_scores_codex":[0.9999143,0.00001777415,0.000004420761,0.0000144649,0.0000359486,0.00001310442],"domain_scores_gemma":[0.9998288,0.00009865879,0.00002483793,0.00001006078,0.00002662874,0.00001101637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002195809,0.00001655072,0.000524712,0.00003589563,0.000006341837,0.00005840405,0.00005175803,0.986549,0.006223397,0.00214119,0.00007233208,0.004298485],"study_design_scores_gemma":[0.00000427975,0.000008215667,0.0001165808,0.000002138883,0.000002718015,0.00002006591,0.000005206497,0.9986166,0.0005993379,0.0004188308,0.0002033346,0.000002759641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2458836,0.0007310802,0.7443213,0.0002202507,0.00005726213,0.00009895085,0.0001539846,0.000316548,0.008217032],"genre_scores_gemma":[0.9530603,0.0005043636,0.04141678,0.00003118653,0.00001756697,0.0001262174,0.0000633717,0.00006732438,0.004712949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007967118,"threshold_uncertainty_score":0.01584148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007052013946154886,"score_gpt":0.1997122404228274,"score_spread":0.1926602264766725,"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."}}