{"id":"W1995207348","doi":"10.1103/physrevlett.112.040406","title":"Weak Value Amplification is Suboptimal for Estimation and Detection","year":2014,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Statistical Mechanics and Entropy","field":"Physics and Astronomy","cited_by":213,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office of Naval Research; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Postselection; Weak measurement; Estimator; Observable; Value (mathematics); Computer science; Noise (video); SIGNAL (programming language); Statistical physics; Algorithm; Statistics; Physics; Mathematics; Quantum; Quantum mechanics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000100826,0.00009415768,0.0001675835,0.00001130262,0.00006997433,0.00002720441,0.00004445515,0.000004660474,0.00002070106],"category_scores_gemma":[0.0000298854,0.0000823669,0.00007038032,0.00005370696,0.00001750716,0.00006281178,0.00001147206,0.00005386253,0.00003184536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009772438,"about_ca_system_score_gemma":0.000002719932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001339531,"about_ca_topic_score_gemma":3.518911e-8,"domain_scores_codex":[0.9994459,0.00002787448,0.0001263483,0.0001863684,0.0000831014,0.000130481],"domain_scores_gemma":[0.9995985,0.0001382807,0.00006708371,0.0001166599,0.00002396247,0.00005550365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007291691,0.00004596065,0.00004700764,0.0003186756,0.00002107085,1.592219e-8,0.00002605699,0.00007665091,0.01097945,0.5814857,0.001735562,0.4052565],"study_design_scores_gemma":[0.0002497755,0.00006525837,0.0004943387,0.0001704062,0.0001145019,2.223818e-7,0.000003134476,0.9425769,0.001853724,0.04267268,0.01163826,0.0001608411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03395508,0.0000881963,0.9627955,0.002634519,0.00005504126,0.0003032858,0.00001607405,0.00001515488,0.0001371503],"genre_scores_gemma":[0.9922332,0.00003710806,0.004820154,0.002469684,0.0002654963,0.0001254213,0.00003130954,0.0000121323,0.000005491172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9582781,"threshold_uncertainty_score":0.3358825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01338381331383725,"score_gpt":0.2917907659795242,"score_spread":0.2784069526656869,"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."}}