{"id":"W2025389484","doi":"10.1016/j.cor.2008.08.008","title":"Scheduling with uncertain durations: Modeling -robust scheduling with constraints","year":2008,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":62,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Enterprise Ireland","keywords":"Mathematical optimization; Computer science; Scheduling (production processes); Dynamic priority scheduling; Job shop scheduling; Schedule; Robustness (evolution); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002775823,0.001596382,0.002306928,0.0008414256,0.0005000441,0.002452936,0.00288741,0.00190358,0.002108359],"category_scores_gemma":[0.01010947,0.001596021,0.001635724,0.001618869,0.001055388,0.00259514,0.001320754,0.001749431,0.0003942761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00238822,"about_ca_system_score_gemma":0.001935505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01420888,"about_ca_topic_score_gemma":0.006281584,"domain_scores_codex":[0.9984723,0.0004940483,0.00009355495,0.0004002032,0.0003322478,0.000207756],"domain_scores_gemma":[0.9959304,0.002350485,0.0009838524,0.0002536797,0.0003042833,0.0001773234],"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":[0.0000186686,0.000007816288,0.00004951749,0.00002143068,0.00001249207,0.00001616423,0.000009402796,0.992085,0.0001503504,0.005799514,0.0001516906,0.001677834],"study_design_scores_gemma":[0.000005136086,0.000005768943,0.00002927993,0.000003070005,0.000006430027,0.000004948344,0.000002470823,0.9954376,0.00006957728,0.004288744,0.0001432115,0.000003830898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01948879,0.0009330043,0.9753668,0.000507618,0.00009719125,0.00006329374,0.0003320625,0.0002067308,0.003004518],"genre_scores_gemma":[0.8815418,0.001995544,0.1095661,0.0001755854,0.0002913812,0.0003030171,0.0005243941,0.0002063167,0.005395829],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01420888,"threshold_uncertainty_score":0.02825236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09082031233015848,"score_gpt":0.3064289784315333,"score_spread":0.2156086661013748,"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."}}