{"id":"W2363437465","doi":"","title":"On CNC Training Based on Inverse Engineering","year":2010,"lang":"en","type":"article","venue":"","topic":"Higher Education and Teaching Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"College of New Caledonia","funders":"","keywords":"Vocational education; Training (meteorology); Process (computing); Engineering management; Engineering; Key (lock); Numerical control; Control (management); Joint (building); Order (exchange); Manufacturing engineering; Computer science; Artificial intelligence; Mechanical engineering; Civil engineering; Business; Pedagogy; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004345194,0.00006631596,0.00005357802,0.0001080407,0.00004582655,0.00006386235,0.0002935026,0.00003321942,0.0001548028],"category_scores_gemma":[0.0001627652,0.00005646547,0.0000274574,0.0001428432,0.00000629359,0.00007626758,0.00001471573,0.0002587703,0.0001165136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001007246,"about_ca_system_score_gemma":0.00004759362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000071144,"about_ca_topic_score_gemma":0.000003007049,"domain_scores_codex":[0.9994887,0.00003439813,0.00006665696,0.0001677453,0.0001187335,0.0001237893],"domain_scores_gemma":[0.9992756,0.0002630801,0.00001477734,0.0003480969,0.00001077611,0.00008768564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001921368,0.0001067907,0.0001572033,0.000004427298,0.000003611609,0.000003989935,0.003016349,0.005906234,0.005819743,0.9155908,0.002304456,0.06708451],"study_design_scores_gemma":[0.0002304654,0.00006175664,0.003699175,0.00001079042,0.000001002609,0.000001904198,0.00001823913,0.9564703,0.00371009,0.0008461853,0.03478347,0.0001666212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07539507,2.299797e-7,0.8843716,0.001711106,0.001727632,0.00003670038,1.189691e-7,0.0003115387,0.03644599],"genre_scores_gemma":[0.5941595,2.06631e-8,0.4034421,0.001808232,0.00004869723,0.000002941404,2.743486e-7,0.000003823195,0.000534473],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9505641,"threshold_uncertainty_score":0.2302595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.032587729030489,"score_gpt":0.2989179823760749,"score_spread":0.2663302533455859,"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."}}