{"id":"W2609163402","doi":"10.1007/s00170-017-0368-0","title":"On modeling tool performance while machining aluminum-based metal matrix composites","year":2017,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Aluminum Alloys Composites Properties","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Volume fraction; Materials science; Machining; Composite material; Particle (ecology); Finite element method; Tool wear; Particle size; Matrix (chemical analysis); Aluminium; Volume (thermodynamics); Metallurgy; Structural engineering; Engineering","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":[0.0003707114,0.000648605,0.0004015446,0.0003956766,0.000468975,0.0008636132,0.0009140975,0.001218081,0.00181784],"category_scores_gemma":[0.001555101,0.0003661127,0.0003967888,0.0004233511,0.0004215008,0.000594259,0.0002958558,0.0004105704,0.0003520383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006611623,"about_ca_system_score_gemma":0.0007265225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01188014,"about_ca_topic_score_gemma":0.009951596,"domain_scores_codex":[0.9998288,0.00002958609,0.000007339209,0.00003213087,0.0000702335,0.00003183052],"domain_scores_gemma":[0.999276,0.0004683684,0.0000735704,0.00004630112,0.0001191059,0.00001666543],"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":[0.00006162067,0.00004965674,0.0009224037,0.00005117769,0.000008005683,0.00005644109,0.00005440791,0.980507,0.01057574,0.0005251792,0.00008519587,0.007103174],"study_design_scores_gemma":[0.00000244058,0.00004371353,0.0002332083,0.000002414876,0.000003337055,0.000007388317,0.00001425252,0.9949833,0.004494267,0.00008067692,0.0001320049,0.000002943952],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8593383,0.0004029906,0.1213119,0.0001440343,0.00004731892,0.0001024268,0.0001941545,0.0005948248,0.01786407],"genre_scores_gemma":[0.9866615,0.0001067858,0.01113466,0.000009690434,0.000003593451,0.00001991694,0.00004499645,0.00005146706,0.001967269],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01188014,"threshold_uncertainty_score":0.02362198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01250007027800296,"score_gpt":0.2406439108442973,"score_spread":0.2281438405662943,"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."}}