{"id":"W4308017471","doi":"10.1103/physrevd.106.105001","title":"Entanglement harvesting: State dependence and covariance","year":2022,"lang":"en","type":"article","venue":"Physical review. D/Physical review. D.","topic":"Quantum Electrodynamics and Casimir Effect","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Perimeter Institute; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Colleges and Universities; Universitat Politècnica de Catalunya; Government of Canada; Innovation, Science and Economic Development Canada; Institut Périmètre de physique théorique; “la Caixa” Foundation","keywords":"Quantum entanglement; Physics; Covariance; Covariant transformation; Detector; Scalar (mathematics); Perturbation theory (quantum mechanics); Scalar field; Perturbation (astronomy); Quantum electrodynamics; Quantum mechanics; State (computer science); Statistical physics; Quantum; Statistics; Mathematics; Optics","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":[0.001401239,0.000398495,0.0006341678,0.0005600655,0.0006257399,0.001291183,0.001098084,0.0006257658,0.001974522],"category_scores_gemma":[0.003492278,0.0002844282,0.0009197228,0.0006220849,0.003005926,0.002507978,0.001505393,0.001605292,0.000255059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001165672,"about_ca_system_score_gemma":0.0006777101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008702094,"about_ca_topic_score_gemma":0.0006109742,"domain_scores_codex":[0.99955,0.00009748136,0.00001671971,0.00009052305,0.000150432,0.00009487441],"domain_scores_gemma":[0.9967306,0.00192032,0.0004303504,0.0005831833,0.000234576,0.0001010785],"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":[0.00004252789,0.00008570192,0.001140421,0.00007365779,0.0000368496,0.0001971303,0.0001054336,0.04674437,0.01586371,0.9275678,0.0005265782,0.007615798],"study_design_scores_gemma":[0.00001388015,0.00006509212,0.002465078,0.00002728366,0.00003325367,0.0002465573,0.00005385828,0.4747136,0.01099121,0.5100591,0.001273626,0.000057495],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4875318,0.002032451,0.4584994,0.001237363,0.0001397282,0.0001056392,0.0001932118,0.0002339073,0.05002658],"genre_scores_gemma":[0.9856619,0.0006749121,0.009513082,0.000123947,0.00004915684,0.00004420158,0.00006682002,0.00006307573,0.003802845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001974522,"threshold_uncertainty_score":0.008457601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01074543375928565,"score_gpt":0.3867549892806152,"score_spread":0.3760095555213295,"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."}}