{"id":"W2511894953","doi":"","title":"Improved algorithms for quantum identification of boolean oracles","year":2009,"lang":"en","type":"article","venue":"Tokyo Tech Research Repository (Tokyo Institute of Technology)","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Oracle; Computer science; Upper and lower bounds; Set (abstract data type); Algorithm; Matching (statistics); Identification (biology); Range (aeronautics); Constant (computer programming); Time complexity; Discrete mathematics; Combinatorics; Theoretical computer science; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001252902,0.0002104468,0.0004363458,0.001140762,0.0008563736,0.0001262074,0.0008669258,0.0002614971,0.00002105027],"category_scores_gemma":[0.0004653621,0.000194558,0.0001738575,0.000420316,0.002136777,0.0004910886,0.000134787,0.0004651797,0.000009182256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001238392,"about_ca_system_score_gemma":0.0002447836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003784726,"about_ca_topic_score_gemma":0.0002613754,"domain_scores_codex":[0.9975138,0.00005844215,0.0009192209,0.0004795406,0.0005368517,0.0004921434],"domain_scores_gemma":[0.9969123,0.00005229039,0.0004125886,0.0008167486,0.001726082,0.00008001633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007223019,0.0003631995,0.00006540986,0.0001373164,0.00006315203,0.000009703448,0.0003801805,0.00000239153,0.5869253,0.3904164,0.001464517,0.02010028],"study_design_scores_gemma":[0.0006138697,0.001093305,0.000431723,0.0001303141,0.00003647227,0.000008676822,0.0007903679,0.001354493,0.8270428,0.07099234,0.09724543,0.0002602162],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870584,0.0005573057,0.0007232632,0.002451218,0.0009621627,0.00155856,0.00006774435,0.0003454707,0.006275886],"genre_scores_gemma":[0.995249,0.00006608776,0.001064035,0.00001068216,0.0002319841,0.000119248,0.00001531985,0.00002196817,0.003221703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.319424,"threshold_uncertainty_score":0.7933845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07396980554448204,"score_gpt":0.3454197733108256,"score_spread":0.2714499677663436,"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."}}