{"id":"W4385359901","doi":"10.1007/978-3-031-38906-1_14","title":"Online Interval Scheduling with Predictions","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Disjoint sets; Competitive analysis; Scheduling (production processes); Upper and lower bounds; Algorithm; Mathematical optimization; Mathematics; Combinatorics","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":[0.001591344,0.001279914,0.00178705,0.0005724396,0.0006770387,0.001802129,0.002524796,0.0009094488,0.01707782],"category_scores_gemma":[0.004990948,0.0006410953,0.0007170072,0.001566,0.0005970323,0.00210332,0.001291451,0.002768062,0.003556194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008940477,"about_ca_system_score_gemma":0.001716312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001794643,"about_ca_topic_score_gemma":0.0016957,"domain_scores_codex":[0.9989693,0.0002095444,0.00004526921,0.0002966223,0.0002765406,0.0002027406],"domain_scores_gemma":[0.997758,0.001228081,0.0001383005,0.0005020131,0.0002074059,0.0001661555],"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":[0.001252111,0.0004750975,0.0003467581,0.0002405765,0.00005144267,0.0001070394,0.00006951245,0.5881761,0.00421675,0.06838645,0.03090614,0.305772],"study_design_scores_gemma":[0.00004520698,0.0001002823,0.00009015647,0.00001504641,0.0000118269,0.00002606127,0.00001370336,0.9532782,0.001183829,0.04228513,0.002939461,0.00001113638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02143524,0.0009755612,0.9404941,0.0005421177,0.0008154816,0.0001641335,0.0007546289,0.003207893,0.03161081],"genre_scores_gemma":[0.6282243,0.0008912586,0.3381756,0.0003739455,0.000953888,0.0003312238,0.001629532,0.0006936967,0.02872657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01707782,"threshold_uncertainty_score":0.05713093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03238855091904636,"score_gpt":0.2731777316503188,"score_spread":0.2407891807312724,"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."}}