{"id":"W2087352629","doi":"10.1103/physrevlett.108.230506","title":"Adiabatic Quantum Algorithm for Search Engine Ranking","year":2012,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":106,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"PageRank; Computer science; Quantum algorithm; Algorithm; Quantum computer; Quantum; Theoretical computer science; Ranking (information retrieval); Adiabatic process; Information retrieval; Physics; Quantum mechanics","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":[0.0006001258,0.0002100611,0.0003926443,0.00005436397,0.0001401979,0.00006352955,0.0006746619,0.000009988402,0.000003717655],"category_scores_gemma":[0.00005248304,0.0001656941,0.0002648083,0.0003876248,0.00003939669,0.0002642108,0.0001747387,0.000239668,0.00007004883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000302267,"about_ca_system_score_gemma":0.00001966889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004149339,"about_ca_topic_score_gemma":3.24889e-8,"domain_scores_codex":[0.9983059,0.000114941,0.0002239318,0.0003285935,0.000335258,0.0006914263],"domain_scores_gemma":[0.998794,0.0004386104,0.00006940024,0.0004600556,0.00003992663,0.0001980217],"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":[7.265845e-7,0.0001315575,0.00001740329,0.0006821707,0.00003631303,0.000003091317,0.0004661274,0.0005957488,0.001137434,0.00512147,0.002626454,0.9891815],"study_design_scores_gemma":[0.0001867119,0.00004633151,0.0001634293,0.0006121241,0.00002707342,0.00001290827,0.000001246768,0.9851146,0.0002719425,0.0004157906,0.01289379,0.0002540983],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02269377,0.008418892,0.9593719,0.008400654,0.0004344655,0.0004953393,0.00000413175,0.0001626498,0.00001822686],"genre_scores_gemma":[0.4950684,0.001020315,0.457845,0.04184043,0.003900031,0.0002112258,0.0000211085,0.00007681284,0.00001670211],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9889274,"threshold_uncertainty_score":0.6756811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01915950580011912,"score_gpt":0.2927217923485285,"score_spread":0.2735622865484094,"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."}}