{"id":"W2950135190","doi":"10.48550/arxiv.1307.8161","title":"Mutually Unbiased Weighing Matrices","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"graph theory and CDMA systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Lethbridge","funders":"","keywords":"Hadamard transform; Mutually unbiased bases; Mathematics; Upper and lower bounds; Best linear unbiased prediction; Computer science; Algorithm; Combinatorics; Statistics; Pure mathematics; Artificial intelligence; Mathematical analysis","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":[0.001695802,0.001101062,0.0007136912,0.001360805,0.001008204,0.001606628,0.0009208473,0.001364101,0.007194442],"category_scores_gemma":[0.0147417,0.0004445753,0.0005093514,0.001134261,0.001574111,0.002834899,0.001667082,0.001710832,0.001756148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005018208,"about_ca_system_score_gemma":0.0005620567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003903762,"about_ca_topic_score_gemma":0.0004552851,"domain_scores_codex":[0.997767,0.0007291006,0.00009245363,0.0004051449,0.0007549909,0.0002513996],"domain_scores_gemma":[0.9926561,0.003835368,0.0007929922,0.001190322,0.001209953,0.0003152558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009255052,0.00003667151,0.0007146231,0.0001297838,0.00004732949,0.0001703798,0.0001347206,0.0305499,0.01460774,0.9061601,0.00311822,0.04423802],"study_design_scores_gemma":[0.00001967178,0.00008748808,0.0004721534,0.00005583261,0.00002747681,0.0004423757,0.00007871723,0.2272963,0.009982776,0.7522264,0.009261704,0.00004905966],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03157774,0.0004585621,0.9501371,0.0003889946,0.0001977134,0.00005911846,0.0001257161,0.000179673,0.01687542],"genre_scores_gemma":[0.7134629,0.001195321,0.2608855,0.0007571727,0.0006410867,0.0002315796,0.0003419204,0.000182793,0.02230171],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007194442,"threshold_uncertainty_score":0.02406776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03665512459433039,"score_gpt":0.1441904254200439,"score_spread":0.1075353008257135,"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."}}