{"id":"W2043464967","doi":"10.1016/j.cirp.2011.03.123","title":"Predictive compliance based model for compensation in multi-pass milling by on-machine probing","year":2011,"lang":"en","type":"article","venue":"CIRP Annals","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Deflection (physics); Machine tool; Deflection angle; Compensation (psychology); Mechanical engineering; Variable (mathematics); Engineering; End milling; Control theory (sociology); Engineering drawing; Structural engineering; Computer science; Machining; Optics; Mathematics; Artificial intelligence; Physics; Mathematical analysis","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":[0.0005300627,0.0006115469,0.001164485,0.0002979502,0.0004426932,0.000934296,0.001221655,0.001623248,0.001885247],"category_scores_gemma":[0.001153393,0.0005354818,0.0005069234,0.000428786,0.0005912932,0.0008553679,0.0006670941,0.001001422,0.0003022815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006978502,"about_ca_system_score_gemma":0.0009373007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009116364,"about_ca_topic_score_gemma":0.007673768,"domain_scores_codex":[0.9996765,0.00007674043,0.0000131653,0.00007540176,0.0001156692,0.00004253323],"domain_scores_gemma":[0.9995912,0.0001981385,0.00005371115,0.00003840236,0.0001065119,0.00001201489],"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":[0.00006477219,0.00003344263,0.0002271556,0.00005153674,0.00001282702,0.00003323238,0.00003173757,0.9815894,0.00303165,0.00159863,0.0003282431,0.01299731],"study_design_scores_gemma":[0.000001927279,0.000007194806,0.0000617775,0.000001319716,0.000001856485,0.000002368279,0.000001204714,0.9994332,0.000280156,0.0001438942,0.00006330533,0.000001792121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04527957,0.000332829,0.9481015,0.0002020401,0.00009674262,0.00005431171,0.00007875403,0.0005801265,0.005273995],"genre_scores_gemma":[0.9765779,0.0001545551,0.01836939,0.00005592685,0.00001664357,0.00008191892,0.00006373139,0.00005117445,0.004628797],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009116364,"threshold_uncertainty_score":0.01812655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1491360141701295,"score_gpt":0.3110478690137052,"score_spread":0.1619118548435757,"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."}}