{"id":"W194540509","doi":"","title":"A Modeling for the Total Tardiness SMSDST Problem Using Constraint Programming.","year":2010,"lang":"en","type":"article","venue":"International Conference on Artificial Intelligence","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Chicoutimi; Université du Québec","funders":"","keywords":"Tardiness; Constraint programming; Computer science; Mathematical optimization; Constraint satisfaction; Constraint (computer-aided design); Concurrent constraint logic programming; Constraint logic programming; Programming language; Job shop scheduling; Stochastic programming; Mathematics; Artificial intelligence; Embedded system; Routing (electronic design automation)","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":[0.001819667,0.001020468,0.0008971825,0.001011036,0.0007727995,0.002367071,0.003432348,0.001486942,0.007131199],"category_scores_gemma":[0.004269744,0.0007597708,0.001930307,0.002053315,0.0007352715,0.001844357,0.001077565,0.002145055,0.0008403335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002668825,"about_ca_system_score_gemma":0.004996845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04467817,"about_ca_topic_score_gemma":0.05169515,"domain_scores_codex":[0.9987692,0.0004630358,0.00006481566,0.0002056571,0.0003208931,0.0001764531],"domain_scores_gemma":[0.9982787,0.001062455,0.0001981582,0.0000977045,0.0002368467,0.0001261779],"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":[0.00004681028,0.00006316673,0.000309636,0.0001427145,0.00003621799,0.0001444485,0.00006081699,0.9213902,0.0005215223,0.06383476,0.003657901,0.009791809],"study_design_scores_gemma":[0.00001199703,0.00001688381,0.00007148895,0.00001909282,0.00001091648,0.00003331286,0.00002847186,0.9801165,0.0001392889,0.01667554,0.002868297,0.000008193721],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01167853,0.0005872667,0.9673436,0.001085569,0.0001581171,0.0002852344,0.001394909,0.0002682594,0.01719866],"genre_scores_gemma":[0.3668702,0.001616154,0.6079632,0.0004417532,0.0002043638,0.0009856331,0.001942753,0.0003382356,0.01963764],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04467817,"threshold_uncertainty_score":0.08883625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1200230154725008,"score_gpt":0.3461662791720779,"score_spread":0.2261432636995771,"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."}}