{"id":"W4409794809","doi":"10.61091/jcmcc127b-525","title":"Research on Constructing Task Scheduling and Processing Models for Complex Data Sets Using Multi-Objective Optimization Algorithm","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Scheduling (production processes); Task (project management); Optimization algorithm; Algorithm; Mathematical optimization; Mathematics; Engineering; Systems engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005403347,0.0003245029,0.000801958,0.0006427264,0.001031309,0.0009490952,0.001235212,0.0002057296,2.158385e-7],"category_scores_gemma":[0.001051376,0.000313833,0.0000731234,0.0008388532,0.0001869287,0.0009396672,0.001189754,0.0007755255,1.412645e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001792047,"about_ca_system_score_gemma":0.0005541401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001073953,"about_ca_topic_score_gemma":7.075488e-8,"domain_scores_codex":[0.996612,0.0002873545,0.001154294,0.0006010577,0.0008065496,0.0005387807],"domain_scores_gemma":[0.9945183,0.002133996,0.001010463,0.0005330143,0.001627165,0.0001771013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001233654,0.0009506731,0.00006612277,0.0009125979,0.0003297156,0.00004462256,0.003750492,0.2901113,0.0005175487,0.6296319,0.00007097163,0.07349067],"study_design_scores_gemma":[0.003413987,0.0002780333,0.000007872094,0.001218536,0.00005519475,0.0000957825,0.0009358496,0.8281271,0.00009244579,0.1655391,0.00001001206,0.0002261697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01182361,0.0003480082,0.9818817,0.0001157567,0.005127049,0.0005328453,0.000007863916,0.00005443763,0.000108733],"genre_scores_gemma":[0.2778722,0.00001156904,0.7217135,0.00001958298,0.0003542647,0.000002012775,0.000003440279,0.00002225503,0.000001109371],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5380158,"threshold_uncertainty_score":0.9999314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1269105992066066,"score_gpt":0.3887798224770101,"score_spread":0.2618692232704035,"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."}}