{"id":"W34978793","doi":"10.1016/b978-008043711-8/50045-3","title":"INTELLIGENT MACHINING SYSTEMS - CHALLENGES AND OPPORTUTINTIES","year":2000,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Machining; Computer science; Manufacturing engineering; Engineering; Mechanical 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009886584,0.0003507604,0.0003776016,0.0001289182,0.00005374168,0.00007111226,0.0001117528,0.000249117,0.0001275497],"category_scores_gemma":[0.00000177171,0.0003406781,0.00005839027,0.000002359457,0.00004237795,0.00003735859,0.00003723943,0.0002943692,0.0000355185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003344846,"about_ca_system_score_gemma":0.00001251561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.198782e-7,"about_ca_topic_score_gemma":0.000002856064,"domain_scores_codex":[0.9990758,0.000006275681,0.0003185035,0.0002585119,0.0001519853,0.0001889745],"domain_scores_gemma":[0.9995813,0.00002012878,0.00006635954,0.0002251745,0.00001949322,0.00008749667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002247072,7.971169e-7,1.338858e-7,0.0007241642,0.00007009055,0.000009431735,0.0005333344,0.003210856,2.093775e-7,0.006167872,0.00001666293,0.9892642],"study_design_scores_gemma":[0.00005733904,0.00001831577,0.000002865642,0.0007875409,0.0000548382,0.00002240097,0.00002456179,0.002724146,0.00002175458,0.002366205,0.9935199,0.0004001393],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00001582266,0.07490677,0.00004272788,0.00000738597,0.0003862588,0.0002142353,0.000009374317,0.0002741489,0.9241433],"genre_scores_gemma":[0.00858721,0.06459175,0.0001271232,0.00001856284,0.0002745849,0.00002909668,0.00002234072,0.0001464885,0.9262028],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9935032,"threshold_uncertainty_score":0.9999045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02428118147792205,"score_gpt":0.2080993286795229,"score_spread":0.1838181472016009,"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."}}