{"id":"W2038713182","doi":"10.1103/physreva.67.062311","title":"Pattern recognition on a quantum computer","year":2003,"lang":"en","type":"article","venue":"Physical Review A","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Speedup; Quantum Fourier transform; Quantum; Computer science; Simple (philosophy); Quantum computer; Fourier transform; Task (project management); Quantum algorithm; Algorithm; Quantum sort; Exponential function; Quantum phase estimation algorithm; Theoretical computer science; Mathematics; Quantum error correction; Parallel computing; Physics; Quantum mechanics; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002027141,0.000161591,0.0002682654,0.00003064537,0.0000769063,0.00005803283,0.000350943,0.0000156142,0.00001012532],"category_scores_gemma":[0.00005237337,0.0001202495,0.0001589621,0.0002901539,0.00001888839,0.00007967679,0.00007037206,0.0002117589,0.0005077578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001373361,"about_ca_system_score_gemma":0.00002148483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002629572,"about_ca_topic_score_gemma":1.393525e-7,"domain_scores_codex":[0.998762,0.0001925532,0.0001673181,0.0003867634,0.0002425885,0.0002488465],"domain_scores_gemma":[0.9992009,0.0001577608,0.00007446214,0.0004259039,0.00004276372,0.00009824062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[4.626966e-7,0.0001836955,0.000007441907,0.0001859851,0.000008476748,0.00001286672,0.00006781279,0.00006583711,0.00001778183,0.01491691,0.001779762,0.982753],"study_design_scores_gemma":[0.000405915,0.0006773382,0.0006161362,0.003838222,0.00002598418,0.0000656415,0.000001010865,0.8391125,0.0005305439,0.08529845,0.0687846,0.0006436522],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0656752,0.002798338,0.9233595,0.004129883,0.00070909,0.0005128187,0.000003537171,0.000394466,0.002417227],"genre_scores_gemma":[0.9539759,0.001106127,0.02482122,0.01930772,0.0006825719,0.00004934401,0.000006626153,0.00002976064,0.00002074275],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9821093,"threshold_uncertainty_score":0.6526369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02209281112414842,"score_gpt":0.2783849534225951,"score_spread":0.2562921422984467,"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."}}