{"id":"W4394565890","doi":"10.1103/physrevlett.132.150201","title":"Every Quantum Helps: Operational Advantage of Quantum Resources beyond Convexity","year":2024,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute; University of Waterloo","funders":"Precursory Research for Embryonic Science and Technology; Core Research for Evolutional Science and Technology; Ministry of Education, Culture, Sports, Science and Technology; Japan Society for the Promotion of Science; Biotechnology and Biological Sciences Research Council; Japan Science and Technology Agency; Engineering and Physical Sciences Research Council; UK Research and Innovation","keywords":"Convexity; Quantum; Computer science; Quantum mechanics; Physics; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003778833,0.0004645446,0.0008849967,0.0009233996,0.001037346,0.003255386,0.001115731,0.001151907,0.005101866],"category_scores_gemma":[0.01337344,0.0003254141,0.0008267834,0.0007387607,0.007302536,0.007267971,0.003370256,0.002348272,0.0003318735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001304581,"about_ca_system_score_gemma":0.0008845621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004441132,"about_ca_topic_score_gemma":0.0002970279,"domain_scores_codex":[0.997165,0.0009947204,0.0001498101,0.0004554342,0.0008337049,0.0004012233],"domain_scores_gemma":[0.9870622,0.007736939,0.0008934365,0.003128104,0.0006685464,0.0005107181],"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":[0.00003728083,0.00001363595,0.0002713342,0.00003784091,0.00001828798,0.00006031531,0.00006888901,0.01278423,0.002150463,0.9795495,0.0003496715,0.004658536],"study_design_scores_gemma":[0.000008364053,0.00003542645,0.0003606716,0.00001768061,0.00001194438,0.0000867601,0.00006342633,0.04228934,0.001732999,0.9540292,0.001344219,0.00002004963],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2892299,0.001271152,0.6256312,0.005075161,0.0001975897,0.00009834705,0.0003861953,0.0003124479,0.07779791],"genre_scores_gemma":[0.9794506,0.0002613614,0.01801623,0.0002188692,0.00006605997,0.00004574108,0.00005307161,0.00006165086,0.001826349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005101866,"threshold_uncertainty_score":0.0199846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01296230969723233,"score_gpt":0.283489767789367,"score_spread":0.2705274580921347,"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."}}