{"id":"W2093784897","doi":"10.1080/00207540410001671697","title":"Production planning for surface mount technology lines","year":2004,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Assembly Line Balancing Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Mount; Production (economics); Production planning; Surface-mount technology; Hierarchy; Operations research; Production line; Engineering; Mathematical model; Industrial engineering; Computer science; Mechanical engineering; Mathematics; Economics","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":[0.0007268307,0.001021644,0.0008819885,0.0005110308,0.0006809706,0.001927829,0.001170119,0.001169977,0.006996086],"category_scores_gemma":[0.001362801,0.0007347419,0.0008568031,0.001023172,0.000811456,0.001421223,0.0007349647,0.001293422,0.001006501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001709711,"about_ca_system_score_gemma":0.001791869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0063879,"about_ca_topic_score_gemma":0.006266757,"domain_scores_codex":[0.9994261,0.0001981146,0.00001797143,0.0001129039,0.0001641813,0.00008066427],"domain_scores_gemma":[0.9995725,0.0002245461,0.00009672806,0.00002265604,0.00005558758,0.000027969],"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":[0.0000238714,0.00001531789,0.0001081527,0.00005446959,0.000005096079,0.00006439005,0.00002783112,0.9687374,0.001062225,0.02166628,0.0007743865,0.007460542],"study_design_scores_gemma":[0.000008809774,0.00004269595,0.00009843467,0.00001290946,0.000004614497,0.00001909259,0.00002183505,0.9848014,0.0006397308,0.01241473,0.001927635,0.000008102789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01019173,0.0002817888,0.9790845,0.0002537953,0.00003205612,0.00009346373,0.0001336354,0.0001452713,0.009783769],"genre_scores_gemma":[0.660317,0.001604361,0.3154961,0.0001138282,0.00006326377,0.0006163356,0.0005063615,0.0001703853,0.02111235],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006996086,"threshold_uncertainty_score":0.02340424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05822485377476629,"score_gpt":0.3944845113907983,"score_spread":0.336259657616032,"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."}}