{"id":"W2079570072","doi":"10.1080/002075400411475","title":"A multi-level heuristic search algorithm for production scheduling","year":2000,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Scheduling (production processes); Mathematical optimization; Computer science; Production (economics); Algorithm; Heuristic; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00247301,0.0001257319,0.0001639642,0.0007008707,0.0001578184,0.0001340607,0.0004191021,0.00008149371,0.0002761557],"category_scores_gemma":[0.0008243512,0.0001226032,0.0001056698,0.0004417532,0.0001179306,0.0004082292,0.00002181497,0.0006159877,0.00007102869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002659532,"about_ca_system_score_gemma":0.0001323168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007083848,"about_ca_topic_score_gemma":0.00000207055,"domain_scores_codex":[0.9976735,0.0001066958,0.0005209277,0.000242565,0.001143811,0.0003124753],"domain_scores_gemma":[0.9961792,0.00009658944,0.00005982784,0.0001672256,0.003375726,0.0001214632],"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":[0.0000861878,0.0001491253,0.00003714273,0.00002529527,0.0001603415,0.0000113674,0.0004481813,0.5048233,0.003251233,0.00001643087,0.001514594,0.4894768],"study_design_scores_gemma":[0.00129394,0.0001631894,0.0005427775,0.0002023683,0.00001998015,0.0005442848,0.0007456181,0.9564227,0.031172,0.0002679327,0.008374538,0.0002505942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1985131,0.00106833,0.7834728,0.005189182,0.01050254,0.0007468756,0.00004228261,0.0001920821,0.000272853],"genre_scores_gemma":[0.1533688,0.001024717,0.8345651,0.00002163491,0.00594094,0.00003940562,0.00002446843,0.00006534909,0.004949555],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4892262,"threshold_uncertainty_score":0.4999613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1215457293275376,"score_gpt":0.3902121092480238,"score_spread":0.2686663799204863,"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."}}