{"id":"W2066228674","doi":"10.1115/1.4025489","title":"Product Design Retrieval by Matching Bills of Materials","year":2013,"lang":"en","type":"article","venue":"Journal of Mechanical Design","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Matching (statistics); Product (mathematics); Tree (set theory); Process (computing); Product design; Data mining; Engineering drawing; Industrial engineering; Engineering; Mathematics; Programming language","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":[0.0008686011,0.0009397043,0.001443419,0.004033159,0.0006459761,0.001359798,0.001456259,0.001397443,0.006916784],"category_scores_gemma":[0.004291133,0.0006343364,0.001490003,0.003986615,0.0004062699,0.001871876,0.001104294,0.0006001473,0.001852715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007401232,"about_ca_system_score_gemma":0.001312052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002047167,"about_ca_topic_score_gemma":0.002307794,"domain_scores_codex":[0.9987715,0.0001813116,0.00007970846,0.0002940848,0.0005855126,0.00008785189],"domain_scores_gemma":[0.9988241,0.0003902116,0.0001976003,0.000294137,0.0002645644,0.00002929256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003097925,0.0001939065,0.003129664,0.0003280147,0.00008151984,0.0001815514,0.0001586363,0.09681359,0.01825384,0.0105126,0.006942076,0.8630947],"study_design_scores_gemma":[0.00006619812,0.0002138955,0.002584141,0.00003033854,0.00006504994,0.0004943561,0.0001204304,0.9386364,0.02355918,0.01463577,0.01953717,0.00005689371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06104475,0.0005592413,0.9282166,0.0001513944,0.00006524281,0.0002949185,0.0006514213,0.003443218,0.005573212],"genre_scores_gemma":[0.1801663,0.0002220983,0.8138035,0.00007231989,0.00002552123,0.0002037051,0.002287389,0.0004277312,0.002791398],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006916784,"threshold_uncertainty_score":0.023139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01871402759967814,"score_gpt":0.2121901240888686,"score_spread":0.1934760964891905,"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."}}