{"id":"W2165175345","doi":"10.24908/pceea.v0i0.3975","title":"TOOL SELECTION-EMBEDDED OPTIMAL ASSEMBLY PLANNING","year":2011,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Selection (genetic algorithm); Plan (archaeology); Task (project management); Computer science; Process (computing); Seven Management and Planning Tools; Systems engineering; Engineering; Operations management; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0006509415,0.001091956,0.0009159676,0.0007451689,0.0004202127,0.0007900399,0.000984648,0.0008039017,0.002606231],"category_scores_gemma":[0.001507808,0.0005931106,0.0007607083,0.0009606252,0.0008982097,0.0008919062,0.001192249,0.0007173865,0.0003537376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006743383,"about_ca_system_score_gemma":0.001180048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002779091,"about_ca_topic_score_gemma":0.002578412,"domain_scores_codex":[0.9991305,0.0002325206,0.00003692769,0.0001367973,0.0003500172,0.0001131811],"domain_scores_gemma":[0.9995642,0.0002482772,0.00005046709,0.00004691273,0.00007042274,0.00001967543],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004510647,0.00003094448,0.0001821155,0.00006721447,0.00001619476,0.00009591379,0.00004872523,0.9513083,0.002165826,0.009450369,0.0004100545,0.03617921],"study_design_scores_gemma":[0.00001544454,0.00005619769,0.0001082685,0.00001324739,0.0000111085,0.00003333577,0.00001694267,0.9846566,0.001443493,0.01210456,0.001531864,0.000008929964],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01745532,0.0002792628,0.975009,0.00005683391,0.00002175696,0.00008858807,0.00004857055,0.0002764004,0.006764215],"genre_scores_gemma":[0.5440367,0.0004593585,0.4503226,0.00005170152,0.00001981303,0.0002558892,0.0002148491,0.0001342152,0.004504798],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002779091,"threshold_uncertainty_score":0.008718729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008099279105180613,"score_gpt":0.1885560531319224,"score_spread":0.1804567740267418,"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."}}