{"id":"W2089305940","doi":"10.1115/1.1826075","title":"Optimal Module Selection for Preliminary Design of Reconfigurable Machine Tools","year":2005,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Computer science; Selection (genetic algorithm); Set (abstract data type); Construct (python library); Component (thermodynamics); Space (punctuation); Feature (linguistics); Engineering drawing; Artificial intelligence; Programming language; Engineering; Operating system","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":[0.0007248037,0.0006077813,0.0008257889,0.001115899,0.0002778547,0.0005472098,0.0007546055,0.0003619931,0.002354068],"category_scores_gemma":[0.001871389,0.0004012494,0.0006288308,0.000596696,0.000355703,0.0006303237,0.0004702474,0.0002559471,0.0003527591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000440694,"about_ca_system_score_gemma":0.0005855932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007331235,"about_ca_topic_score_gemma":0.001048672,"domain_scores_codex":[0.9992858,0.0002009006,0.00004105998,0.0001292974,0.0002659648,0.00007696164],"domain_scores_gemma":[0.9993452,0.0003233913,0.00008861553,0.00009025911,0.0001305272,0.00002192039],"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":[0.0003952612,0.0001799541,0.003083435,0.000297503,0.00008239165,0.0002826489,0.0002379945,0.5281683,0.05900629,0.01473964,0.001426564,0.3921001],"study_design_scores_gemma":[0.00006176672,0.0005210522,0.001683762,0.00003557754,0.00004305318,0.0002453935,0.00009103587,0.94429,0.03637996,0.009748982,0.006866419,0.00003300574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07971427,0.0001777706,0.9171364,0.000029452,0.000007949101,0.00009483351,0.0000708493,0.0003601739,0.002408305],"genre_scores_gemma":[0.5192636,0.0000972587,0.4788192,0.00002681421,0.00000709181,0.0001835456,0.000237603,0.00007922747,0.001285758],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002354068,"threshold_uncertainty_score":0.007875085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01395460516650828,"score_gpt":0.2109646600061553,"score_spread":0.197010054839647,"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."}}