{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002056656,0.00009781193,0.000155008,0.0001071361,0.00002240143,0.00003233182,0.00003101817,0.00008602603,0.000001869613],"category_scores_gemma":[0.0000972003,0.00009339956,0.00002876035,0.0002100128,0.000002518838,0.0002297642,0.000005616425,0.0002272287,1.736573e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007203064,"about_ca_system_score_gemma":0.000007580763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.674868e-7,"about_ca_topic_score_gemma":7.327102e-7,"domain_scores_codex":[0.9993873,0.000006989787,0.0003082487,0.0000717794,0.00009457878,0.0001311084],"domain_scores_gemma":[0.9998154,0.00001516443,0.00002266642,0.00004261805,0.00004289628,0.00006125774],"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":[0.000002148275,0.000005224291,0.000004590766,0.00003211242,0.000004928884,0.000004983151,0.00002465222,0.8622621,0.1365932,0.0005538023,0.000002678779,0.0005096375],"study_design_scores_gemma":[0.0002614078,0.0000256121,0.000004928995,0.00008135277,0.000006569448,0.00007752493,0.00001568914,0.9838554,0.01534346,0.00009769418,0.0001317263,0.00009860691],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3135987,0.001745469,0.6843479,0.00001207685,0.0002394682,0.00002586228,0.000001205561,0.00002517453,0.000004196599],"genre_scores_gemma":[0.983151,0.0007256783,0.01599858,0.000005916798,0.00009324658,0.000001178449,0.000005468318,0.00001801917,9.744559e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6695522,"threshold_uncertainty_score":0.3808724,"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."}}