{"id":"W2061931240","doi":"10.1115/detc2003/dac-48722","title":"Dimensional Adjustment for Assemblability of Rapid Protoyped Parts","year":2003,"lang":"en","type":"article","venue":"","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Rapid prototyping; Computer science; Monte Carlo method; Reliability engineering; Functional requirement; Engineering drawing; Algorithm; Engineering; Software engineering; Mechanical engineering; Mathematics","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":[0.00009130671,0.00005627215,0.00007875,0.00001651807,0.00001395288,0.000003369687,0.00002371581,0.00002784719,0.0002708764],"category_scores_gemma":[0.00002459587,0.00004645886,0.00002634672,0.00002779565,0.000006184225,0.00003729983,0.000003235589,0.00001873366,0.000001585372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000125607,"about_ca_system_score_gemma":0.000009243234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001206062,"about_ca_topic_score_gemma":0.000001205749,"domain_scores_codex":[0.9996551,0.000006030711,0.0001208471,0.00007342295,0.00006090022,0.00008370015],"domain_scores_gemma":[0.9998146,0.00002607085,0.00001429048,0.00008436933,0.00003693653,0.00002374026],"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":[0.00002688161,0.0001409134,0.0004359545,0.0009684369,0.00005006064,1.377075e-7,0.00009848157,0.974257,0.001701814,0.008612418,0.00263377,0.01107415],"study_design_scores_gemma":[0.0009320299,0.0001393405,0.003195602,0.0000246703,0.00002153326,0.000001047603,0.00001788757,0.1638114,0.8076894,0.001969385,0.0219533,0.0002443887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.401495,0.0007431062,0.5489686,0.0000918884,0.0009845488,0.004956501,0.0000229027,0.0006222299,0.04211525],"genre_scores_gemma":[0.9814392,0.000007439689,0.01816845,0.000013687,0.000011279,0.0001709784,0.00000629954,0.000009021227,0.0001736944],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8104456,"threshold_uncertainty_score":0.2965906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01434139664099359,"score_gpt":0.2237197677973221,"score_spread":0.2093783711563285,"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."}}