{"id":"W3037474762","doi":"10.1108/aa-03-2019-0040","title":"Optimization of fastener pattern in airframe assembly","year":2020,"lang":"en","type":"article","venue":"Assembly Automation","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Fastener; Airframe; Simulated annealing; Engineering; Exploit; Computer science; Fuselage; Probabilistic logic; Mathematical optimization; Algorithm; Artificial intelligence; 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":[0.00007684428,0.0001144452,0.0001569143,0.0001004359,0.00001631158,0.00002841734,0.00009326445,0.00009334104,0.00004010616],"category_scores_gemma":[0.00003440365,0.000122737,0.00002980696,0.000267782,0.000006120634,0.0003498638,0.00001587585,0.00008242966,0.00001374698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003321987,"about_ca_system_score_gemma":0.00001161523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001332634,"about_ca_topic_score_gemma":0.000006127612,"domain_scores_codex":[0.9992416,0.00002050733,0.0003130247,0.0001349442,0.0001586939,0.0001312317],"domain_scores_gemma":[0.999719,0.00002274902,0.00007366358,0.00009748134,0.00004422673,0.00004286006],"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":[0.000002427993,0.00001113708,0.0006359442,0.0001767085,0.000007331606,8.789191e-7,0.0004503802,0.9859192,0.001197045,0.00004111041,0.00008765689,0.0114702],"study_design_scores_gemma":[0.0002567246,0.00002498573,0.007846107,0.0000418847,0.000007093421,5.208757e-7,0.00003651432,0.9719013,0.01967974,0.00001831054,0.00006534604,0.0001214625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2216449,0.00004312558,0.7756639,0.0002370971,0.00009929588,0.0001481944,0.000003304446,0.0003459748,0.001814241],"genre_scores_gemma":[0.9937969,0.00002851026,0.005940436,0.0000900275,0.00004308454,0.00001526677,0.00005246711,0.00002716789,0.000006142592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7721519,"threshold_uncertainty_score":0.5005071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01085751961577481,"score_gpt":0.2090846639091889,"score_spread":0.1982271442934141,"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."}}