{"id":"W2123428140","doi":"","title":"The makespan problem of scheduling multi groups of jobs on multi processors at different speeds","year":2012,"lang":"en","type":"article","venue":"Algorithmic operations research","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Job shop scheduling; Computer science; Scheduling (production processes); Mathematical optimization; Upper and lower bounds; Parallel computing; Mathematics; Computer network; Routing (electronic design automation)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001031741,0.0001898239,0.0002334785,0.0002864108,0.0005063858,0.00006842256,0.0003665124,0.0001221589,0.00005707833],"category_scores_gemma":[0.0002161307,0.0001370251,0.0000735809,0.0006733932,0.0002088706,0.0001774491,0.0001100974,0.0004760856,0.0000637975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001657431,"about_ca_system_score_gemma":0.00004430884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004714151,"about_ca_topic_score_gemma":0.00009503422,"domain_scores_codex":[0.99787,0.0001690559,0.0005017125,0.0001993716,0.0006704552,0.0005894399],"domain_scores_gemma":[0.9985766,0.0003020209,0.00003414927,0.0004118716,0.0005156363,0.0001596995],"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":[0.00003300818,0.0006106104,0.003639718,0.0002050458,0.0001646885,0.000001016424,0.0042787,0.9615043,0.01235893,0.001894816,0.00008371299,0.01522542],"study_design_scores_gemma":[0.0006478056,0.00007809047,0.00257462,0.00007947412,0.00001101947,0.000003735352,0.0009345783,0.9511015,0.04425909,0.000007960673,0.0001454321,0.0001567194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9221289,0.001678059,0.07355894,0.0002950097,0.0004156941,0.001164259,0.00004625128,0.0001573462,0.0005555343],"genre_scores_gemma":[0.8467963,0.0003516263,0.151364,0.000005745211,0.0001568854,0.0001433072,0.00002901799,0.00005275123,0.00110034],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07780511,"threshold_uncertainty_score":0.5587721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0685321649947203,"score_gpt":0.3414718059983619,"score_spread":0.2729396410036416,"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."}}