{"id":"W2019658260","doi":"10.1103/physrevlett.104.063603","title":"Machine Learning for Precise Quantum Measurement","year":2010,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":196,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Scheme (mathematics); Quantum; Interferometry; Artificial intelligence; Algorithm; Machine learning; Physics; Mathematics; 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":[0.0005135502,0.0001272293,0.0002107282,0.000042299,0.0001071447,0.00007343006,0.0005093317,0.000007254002,0.00001239731],"category_scores_gemma":[0.0001441802,0.00009942028,0.000234131,0.0002454447,0.00003028122,0.0003552021,0.00006076049,0.0002487485,0.0001079171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001082165,"about_ca_system_score_gemma":0.00001612296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003520984,"about_ca_topic_score_gemma":0.000001334389,"domain_scores_codex":[0.9989283,0.0000415396,0.0002161072,0.000195639,0.0003982089,0.0002202024],"domain_scores_gemma":[0.9992864,0.00006863289,0.0001146901,0.0003394434,0.00009327898,0.00009762432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001441582,0.0004630691,0.0003174901,0.002628523,0.00009061271,0.000002557646,0.0006101557,0.0001693106,0.09106414,0.6396204,0.03822117,0.2267981],"study_design_scores_gemma":[0.0004245827,0.00009437359,0.0004436405,0.000403547,0.00003434774,0.000004422185,0.000001832148,0.3636399,0.001087163,0.003728311,0.62977,0.0003679344],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02238287,0.003074204,0.9438734,0.02785377,0.0006323399,0.001107167,0.000002764917,0.0003674902,0.0007060145],"genre_scores_gemma":[0.9658366,0.0008548778,0.006662154,0.02623856,0.0001768612,0.0002058531,0.000007588812,0.00001324797,0.000004216618],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9434538,"threshold_uncertainty_score":0.4054241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02698986723165562,"score_gpt":0.2801626107507826,"score_spread":0.2531727435191269,"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."}}