{"id":"W4394064432","doi":"10.2316/j.2024.201-0405","title":"APPLICATION OF CNC MACHINING FOR ELECTROMECHANICAL PARTS BASED ON MACHINE VISION TECHNOLOGY, 156-165.","year":2024,"lang":"en","type":"article","venue":"Mechatronic systems and control","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Machining; Numerical control; Machine vision; Engineering drawing; Manufacturing engineering; Computer vision; Computer science; Engineering; Artificial intelligence; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002422905,0.0001550547,0.0002519764,0.0001714571,0.00006030239,0.00003907496,0.00007920696,0.0001279443,0.000002575125],"category_scores_gemma":[0.00001827615,0.0001345988,0.00005125338,0.0001630538,0.00001312706,0.0000708699,0.000007829166,0.000144721,0.000001716562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005041391,"about_ca_system_score_gemma":0.0000213285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000811107,"about_ca_topic_score_gemma":0.000003785891,"domain_scores_codex":[0.9991511,0.00001332257,0.0002691259,0.0002464201,0.0001044862,0.00021559],"domain_scores_gemma":[0.9996002,0.0001135572,0.00004849886,0.0001671195,0.00003388782,0.00003673452],"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":[0.00009868048,0.00002871655,0.00004138166,0.001102382,0.00007493461,0.000001223543,0.00003062031,0.7506015,0.01072318,0.1296593,0.00004269517,0.1075954],"study_design_scores_gemma":[0.0007942848,0.0003320082,0.000003138659,0.0001880936,0.00004629784,0.000005240763,0.00002074233,0.9919224,0.0007388666,0.002128672,0.003692664,0.0001275405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000714625,0.01070589,0.9870234,0.0001722134,0.0002497074,0.0005969031,0.00003688193,0.0004140169,0.00008641476],"genre_scores_gemma":[0.998025,0.0000694272,0.001374425,0.00002199746,0.00006967131,0.0003519821,0.00002602237,0.00004348402,0.00001797466],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9973104,"threshold_uncertainty_score":0.548878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002621170030004999,"score_gpt":0.2221454152562177,"score_spread":0.2195242452262127,"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."}}