{"id":"W2625051394","doi":"10.1145/3107548","title":"Deep optimization for spectrum repacking","year":2017,"lang":"en","type":"article","venue":"Communications of the ACM","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Spectrum auction; Solver; Reuse; The Internet; Telecommunications link; Distributed computing; Mathematical optimization; Computer network; Auction theory; Operating system; Common value auction","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":[0.002108952,0.00106527,0.0009320101,0.000626253,0.0006674461,0.001359464,0.001459582,0.001101778,0.007838043],"category_scores_gemma":[0.006174982,0.0008448674,0.001111236,0.0006535829,0.001764211,0.001710046,0.00218281,0.002231789,0.0006758229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001719245,"about_ca_system_score_gemma":0.002532001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007548766,"about_ca_topic_score_gemma":0.01351152,"domain_scores_codex":[0.9987659,0.0005143155,0.00004835716,0.0002122964,0.0002238005,0.0002352867],"domain_scores_gemma":[0.9974743,0.001862411,0.0001321291,0.0002123418,0.0002392063,0.00007958474],"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":[0.0001347663,0.0001039056,0.001215735,0.0001458467,0.00005237414,0.00007473827,0.00008475686,0.9074937,0.001613555,0.03487505,0.003020728,0.05118496],"study_design_scores_gemma":[0.00002391639,0.00003095604,0.00008776419,0.00001345077,0.000009462601,0.00001162194,0.00002590651,0.9779235,0.0007048753,0.01970539,0.001458469,0.00000457086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06533166,0.0006061691,0.9135585,0.0009718872,0.0001163453,0.0001876401,0.0003282302,0.002384364,0.0165153],"genre_scores_gemma":[0.5260485,0.0002411373,0.4651549,0.0005109335,0.00003612938,0.0002710639,0.0006080128,0.0005229023,0.006606428],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007838043,"threshold_uncertainty_score":0.02622086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2709712926747263,"score_gpt":0.4669176880769768,"score_spread":0.1959463954022505,"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."}}