{"id":"W2979799318","doi":"10.1103/physrevlett.123.150401","title":"How to Quantify a Dynamical Quantum Resource","year":2019,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum Information and Cryptography","field":"Computer Science","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"European Regional Development Fund; Natural Sciences and Engineering Research Council of Canada; Ministerio de Economía y Competitividad; Generalitat de Catalunya","keywords":"Smoothing; Exponent; Statistical physics; Lemma (botany); Entropy (arrow of time); Kullback–Leibler divergence; Quantum relative entropy; Quantum; Mathematics; Applied mathematics; Computer science; Discrete mathematics; Physics; Quantum mechanics; Quantum discord; Quantum entanglement; Statistics","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":[0.002434102,0.0004483637,0.0005638336,0.0009948398,0.0008376098,0.002331326,0.0009133249,0.001120197,0.003724836],"category_scores_gemma":[0.008051634,0.000330663,0.0004882453,0.0008051651,0.004906157,0.009534633,0.002198833,0.001562384,0.0004369758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001211667,"about_ca_system_score_gemma":0.0009802586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001013691,"about_ca_topic_score_gemma":0.000603815,"domain_scores_codex":[0.9989293,0.0002930572,0.0000810335,0.0002627945,0.0003175444,0.0001162392],"domain_scores_gemma":[0.9966334,0.00159507,0.0004001956,0.0007459723,0.0004061754,0.0002192435],"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":[0.000009000395,0.000006996065,0.0001751999,0.00002445581,0.000008729466,0.00001659066,0.00005598232,0.008627358,0.00116095,0.9853966,0.0002873146,0.004230818],"study_design_scores_gemma":[0.000003182214,0.00001754335,0.0002136616,0.00001924321,0.000004669283,0.00004445892,0.00004889898,0.0525809,0.001056286,0.9436159,0.002373495,0.00002187179],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07669941,0.0006300695,0.8979275,0.002583732,0.0001975093,0.00005381836,0.0002145446,0.0001479584,0.02154546],"genre_scores_gemma":[0.841215,0.0006014314,0.1523685,0.0003943411,0.0002027595,0.0001018684,0.0001432183,0.0001232605,0.004849627],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003724836,"threshold_uncertainty_score":0.01287293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267850142180719,"score_gpt":0.2648064184951495,"score_spread":0.2521279170733423,"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."}}