{"id":"W3176848776","doi":"10.1613/jair.1.14117","title":"Contract Scheduling with Predictions","year":2023,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence Research","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Centre National de la Recherche Scientifique; Agence Nationale de la Recherche","keywords":"Computer science; Imperfect; Scheduling (production processes); Robustness (evolution); Schedule; Binary number; Operations research; Mathematical optimization; Machine learning; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.006498144,0.001097672,0.001464454,0.0004787961,0.0008369026,0.001819347,0.002033362,0.001150599,0.004287748],"category_scores_gemma":[0.02787318,0.0005929874,0.0006727644,0.0008281711,0.002037731,0.003046023,0.001782083,0.002484365,0.0006142843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001588281,"about_ca_system_score_gemma":0.003098185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002924411,"about_ca_topic_score_gemma":0.001916724,"domain_scores_codex":[0.9962942,0.001292142,0.0002246301,0.0007189418,0.0009742731,0.0004958615],"domain_scores_gemma":[0.9825822,0.00988666,0.001837657,0.00362318,0.001244366,0.0008258486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006816554,0.0001198853,0.001497735,0.000120771,0.00005330636,0.0001981406,0.000223289,0.8304723,0.002764277,0.1228685,0.002426236,0.03857395],"study_design_scores_gemma":[0.00003378891,0.00007149438,0.0001334238,0.000008723364,0.000008507223,0.00002959952,0.00001562148,0.9553723,0.0008735561,0.0424116,0.001029293,0.00001210897],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0602324,0.0003546535,0.9327376,0.0005099234,0.0001530995,0.0001933388,0.0002809361,0.0005925711,0.004945485],"genre_scores_gemma":[0.9173015,0.0002371714,0.07796504,0.0001307107,0.0001332778,0.0001433007,0.0002451391,0.0001117508,0.003732011],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006498144,"threshold_uncertainty_score":0.03436589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5279592051656413,"score_gpt":0.563474215626612,"score_spread":0.03551501046097072,"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."}}