{"id":"W2891371211","doi":"10.1103/physrevlett.122.140402","title":"Operational Advantage of Quantum Resources in Subchannel Discrimination","year":2019,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":140,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute","funders":"Air Force Office of Scientific Research; Intelligence Advanced Research Projects Activity; Army Research Office; Templeton Religion Trust; Zhejiang University; H2020 European Research Council; Ontario Ministry of Research, Innovation and Science; Government of Canada; National Science Foundation","keywords":"Computer science; Quantum entanglement; Robustness (evolution); Quantum; Resource (disambiguation); Resource dependence theory; Theoretical computer science; Statistical physics; Quantum mechanics; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003136431,0.0005426435,0.0006195466,0.0009156164,0.0006835076,0.00259631,0.0008905398,0.0008797915,0.004264396],"category_scores_gemma":[0.009742864,0.0002704879,0.0007146809,0.0006445282,0.005738784,0.005640469,0.003314342,0.002213204,0.0002721359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001264375,"about_ca_system_score_gemma":0.00073765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005118838,"about_ca_topic_score_gemma":0.0003211079,"domain_scores_codex":[0.9975121,0.0008812617,0.0001367344,0.0003999101,0.0006712545,0.0003986541],"domain_scores_gemma":[0.9911692,0.006175763,0.0006829355,0.001116013,0.0004073773,0.0004486114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004550577,0.00001589434,0.0001955385,0.00003143069,0.00001138707,0.00004214403,0.00007697697,0.009998861,0.002336369,0.9830851,0.0002026068,0.003958056],"study_design_scores_gemma":[0.00001016083,0.00003781072,0.0003204286,0.00001643343,0.0000112904,0.00006034563,0.00005384057,0.05958628,0.001983103,0.9369998,0.0008967915,0.0000236706],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3685648,0.001150213,0.5582193,0.002000448,0.0001731009,0.00009634277,0.0002798705,0.0002708766,0.069245],"genre_scores_gemma":[0.9803885,0.0002320786,0.01729258,0.0001417208,0.00007379435,0.00005621602,0.00004929994,0.00004711398,0.001718747],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004264396,"threshold_uncertainty_score":0.0165872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01082431231318544,"score_gpt":0.270183681929755,"score_spread":0.2593593696165696,"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."}}