{"id":"W2100308419","doi":"10.1016/s0004-3702(00)00035-7","title":"Constraint-directed techniques for scheduling alternative activities","year":2000,"lang":"en","type":"article","venue":"Artificial Intelligence","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Scheduling (production processes); Mathematical optimization; Schedule; Constraint programming; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001256921,0.000134028,0.0001325433,0.00007391552,0.00009780614,0.00007141638,0.0001308181,0.00007132056,0.0004469537],"category_scores_gemma":[0.00005764272,0.0001439866,0.00005669543,0.0001735497,0.00008980292,0.0001409369,0.000005936693,0.0001155419,0.00005629892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003372485,"about_ca_system_score_gemma":0.00001218622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001421552,"about_ca_topic_score_gemma":0.000009687492,"domain_scores_codex":[0.9992536,0.00001401334,0.0002426195,0.0001699262,0.00009391298,0.000225874],"domain_scores_gemma":[0.9995958,0.000143902,0.00002137019,0.0001222507,0.0000620103,0.00005469997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001970751,0.00002327024,0.000003695803,0.0000133006,0.00002855321,0.000001640469,0.0005545035,0.2518945,0.001770303,0.003300983,0.0000488995,0.7423406],"study_design_scores_gemma":[0.0000103419,0.00002219247,8.217268e-7,0.00002237424,0.000005621127,0.000002371114,0.0002974642,0.6385434,0.3558256,0.004577777,0.0005564491,0.0001355233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04319161,0.0001034846,0.950395,0.0001269298,0.0003570584,0.0002856867,0.00002534175,0.001632662,0.003882156],"genre_scores_gemma":[0.6871153,0.0001094548,0.3121665,0.00009519869,0.0002670305,0.00008032668,0.0000128791,0.0000327051,0.0001205736],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7422051,"threshold_uncertainty_score":0.5871605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03535660262591858,"score_gpt":0.2865996582321427,"score_spread":0.2512430556062241,"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."}}