{"id":"W1824513792","doi":"10.1007/s00170-015-7919-z","title":"Force model for impact cutting grinding with a flexible robotic tool holder","year":2015,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hydro-Québec; École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Grinding; Mechanical engineering; Chip; Energy consumption; Process (computing); Specific energy; Energy (signal processing); Grinding wheel; Computer science; Automotive engineering; Materials science; Engineering; Process engineering; Mathematics","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":[0.0001775911,0.0001554629,0.0001906019,0.0002748539,0.00005783657,0.00004390289,0.0005511893,0.00006535286,0.000002249294],"category_scores_gemma":[0.0001102208,0.0001028188,0.00006416624,0.00007489287,0.00003934074,0.0004257731,0.00006182004,0.0002814149,8.611059e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001866778,"about_ca_system_score_gemma":0.00005769595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.087464e-7,"about_ca_topic_score_gemma":0.000002688331,"domain_scores_codex":[0.9991387,0.000003545009,0.0002970787,0.000104283,0.0002351327,0.0002212594],"domain_scores_gemma":[0.9992523,0.00006574425,0.0002297304,0.0001364942,0.0002727242,0.00004300741],"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":[0.0001584469,0.000009268958,0.00007154844,0.00001187817,0.0001094695,0.000004840957,0.0001538335,0.9865263,0.001184359,0.0005719844,0.00003830962,0.01115983],"study_design_scores_gemma":[0.001800706,0.00024529,0.00004636764,0.0001617124,0.00004377946,0.0004936401,0.0003201084,0.827382,0.1283296,0.04061,0.000340989,0.0002257509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3041754,0.0001668458,0.6947081,0.0003735829,0.0002533459,0.0001054642,0.00000241997,0.000140868,0.00007397957],"genre_scores_gemma":[0.8585778,0.00006738154,0.1410739,0.00003674393,0.00009585232,0.00001275799,0.00000268847,0.00003673359,0.00009608946],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5544024,"threshold_uncertainty_score":0.419283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01754593603381953,"score_gpt":0.2784590027877211,"score_spread":0.2609130667539016,"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."}}