{"id":"W2963223250","doi":"10.48550/arxiv.1706.03304","title":"Deep Optimization for Spectrum Repacking","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Simons Institute for the Theory of Computing, University of California Berkeley","keywords":"Computer science; Solver; Spectrum auction; The Internet; Software; Domain (mathematical analysis); Distributed computing; Operating system; Auction theory; Common value auction; Economics; Programming language","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":[0.002226547,0.001051597,0.00101172,0.0005903148,0.0006160543,0.001391339,0.001453184,0.001326017,0.008951887],"category_scores_gemma":[0.00764341,0.0007832111,0.001006502,0.0006501721,0.001594774,0.001626276,0.001885776,0.002405121,0.0006882187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001684768,"about_ca_system_score_gemma":0.002407462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00783639,"about_ca_topic_score_gemma":0.01300484,"domain_scores_codex":[0.99892,0.0004772343,0.00004282216,0.0001629609,0.0001858727,0.0002110617],"domain_scores_gemma":[0.9967346,0.002572106,0.0001403968,0.0001963912,0.0002497966,0.0001067256],"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":[0.00008051164,0.00005985342,0.0007621231,0.00008371215,0.00002885344,0.00004729114,0.00004319537,0.9587035,0.0005213187,0.01886477,0.002024947,0.0187799],"study_design_scores_gemma":[0.00001761954,0.00001773532,0.00005486033,0.000008195096,0.000004574335,0.000007239647,0.00001701062,0.9875003,0.0002527359,0.01134518,0.0007719279,0.000002672951],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09762434,0.00081632,0.8737168,0.001387074,0.0001678924,0.000199296,0.0005652531,0.002226415,0.02329652],"genre_scores_gemma":[0.6597188,0.0002661911,0.3310995,0.0005193049,0.00004672929,0.000277352,0.0007754953,0.0005161652,0.006780346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008951887,"threshold_uncertainty_score":0.02994698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2513717293553552,"score_gpt":0.2929160145224907,"score_spread":0.04154428516713549,"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."}}