{"id":"W2595897898","doi":"","title":"Design and automatic assembly sequence generation of a d.c. motor","year":2014,"lang":"en","type":"article","venue":"International Journal of Vehicle Design","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Automotive industry; Engineering; Process (computing); Manufacturing engineering; Production (economics); Torque; Design for assembly; Automotive engineering; Sequence (biology); Industrial engineering; Control engineering; Computer science; Mechanical engineering","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":[0.0004388892,0.00006931899,0.0001136377,0.0001240527,0.00001579,0.00004626203,0.0001488154,0.00003693322,0.00001766977],"category_scores_gemma":[0.00007781883,0.00006296565,0.00002513711,0.00003613101,0.00001509914,0.0002441177,0.000008817813,0.00006662469,0.000001529143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003622136,"about_ca_system_score_gemma":0.00002204894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002133841,"about_ca_topic_score_gemma":1.77233e-7,"domain_scores_codex":[0.999288,0.00005476495,0.0002979063,0.00005250945,0.0002430558,0.00006374477],"domain_scores_gemma":[0.9994233,0.0001134268,0.0001517017,0.00004715309,0.0002262115,0.00003824127],"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":[0.00002071198,0.00001655939,0.00004302644,0.00002614926,0.00005898072,0.000004581187,0.0001669685,0.7988384,0.1633735,0.0001414124,0.000169268,0.03714039],"study_design_scores_gemma":[0.0002710925,0.00009769898,0.0004107167,0.00005002905,0.00001106543,0.00003430688,0.000004112428,0.8735858,0.1251269,0.0002955638,0.00005861746,0.00005405753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2059432,0.0000835664,0.7935915,0.00005985464,0.0002165795,0.00004942143,7.214223e-7,0.00001745463,0.00003773474],"genre_scores_gemma":[0.908718,0.00008184154,0.09102119,0.00002666515,0.0001275711,0.000002073335,8.499933e-7,0.00001032567,0.00001142609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7027749,"threshold_uncertainty_score":0.2567665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03785650517583584,"score_gpt":0.2533704892445457,"score_spread":0.2155139840687099,"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."}}