{"id":"W4249919375","doi":"10.32920/ryerson.14663754.v1","title":"Worst-case & average-case Efficiency trade-offs for search problems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mathematical optimization; Computer science; Set (abstract data type); Search theory; Operations research; Unit (ring theory); Work (physics); Mathematics; Engineering; Economics; Microeconomics","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":[0.008929962,0.002019472,0.002047459,0.001831237,0.001263533,0.004083774,0.002681538,0.00217108,0.006024801],"category_scores_gemma":[0.04616254,0.0009435743,0.001797392,0.002731197,0.002722871,0.007060067,0.002067531,0.003484699,0.0007691954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003314936,"about_ca_system_score_gemma":0.001839077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001192042,"about_ca_topic_score_gemma":0.001268432,"domain_scores_codex":[0.9915375,0.003684556,0.0003928765,0.001254914,0.001918621,0.001211555],"domain_scores_gemma":[0.9430702,0.04829302,0.002618722,0.003314025,0.001813259,0.0008906989],"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":[0.0004448577,0.0003032415,0.001800216,0.0004398857,0.0001993024,0.0001398108,0.0001410914,0.8060905,0.002306022,0.1517615,0.004202796,0.03217065],"study_design_scores_gemma":[0.00004295049,0.0001018441,0.0006748569,0.00005035159,0.00005354091,0.000123284,0.00006960039,0.8548645,0.001582318,0.1403275,0.002084923,0.00002430716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08932567,0.00526556,0.8762717,0.002580224,0.0001961267,0.000138956,0.0004879933,0.00033917,0.02539465],"genre_scores_gemma":[0.7906313,0.002932783,0.1955024,0.0004942944,0.0005255538,0.00045779,0.0006376749,0.001000234,0.007817994],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008929962,"threshold_uncertainty_score":0.04722673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07756221973192895,"score_gpt":0.3166777557122791,"score_spread":0.2391155359803501,"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."}}