{"id":"W2611309753","doi":"10.1103/physrevd.96.016012","title":"Pulse shape optimization for electron-positron production in rotating fields","year":2017,"lang":"en","type":"article","venue":"Physical review. D/Physical review. D.","topic":"Laser-Plasma Interactions and Diagnostics","field":"Physics and Astronomy","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; University of Waterloo","funders":"Fonds de recherche du Québec – Nature et technologies; H2020 European Research Council; Canada Foundation for Innovation; Université de Sherbrooke; National Science Foundation","keywords":"Pair production; Physics; Differential evolution; Polarization (electrochemistry); Electric field; Positron; Electron; Fourier transform; Metaheuristic; Spline (mechanical); Computational physics; Mathematical optimization; Computer science; Algorithm; Mathematics; Quantum mechanics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003022377,0.00039675,0.0009451242,0.00004093461,0.0004043771,0.0001395396,0.000464845,0.00003373409,0.0002083605],"category_scores_gemma":[0.001037072,0.0003404962,0.0005425695,0.0002148438,0.00006408231,0.0006609859,0.0001172003,0.0004698951,0.0002461925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006476597,"about_ca_system_score_gemma":0.00007553431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001111749,"about_ca_topic_score_gemma":0.00001137054,"domain_scores_codex":[0.9977936,0.0001156437,0.0005929426,0.0006694638,0.0002966585,0.0005316733],"domain_scores_gemma":[0.9977577,0.0003979458,0.0005879492,0.0008467568,0.0002514739,0.0001581434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001904809,0.008954632,0.03417355,0.0186843,0.0004482815,0.000009827984,0.0002537492,0.01057669,0.007920934,0.08419625,0.03773702,0.7968543],"study_design_scores_gemma":[0.003882321,0.002065555,0.0126347,0.06880527,0.003355417,0.00001078563,0.00005234245,0.6149287,0.08454879,0.1326568,0.07254612,0.004513199],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9729896,0.002744389,0.002305176,0.006440298,0.0006051077,0.004571388,0.00008038303,0.00008334011,0.01018034],"genre_scores_gemma":[0.987004,0.007877644,0.001192774,0.0005247903,0.001765746,0.00123821,0.0002008162,0.00005676886,0.0001392869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7923411,"threshold_uncertainty_score":0.9999047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01663914300613046,"score_gpt":0.4109504512006406,"score_spread":0.3943113081945101,"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."}}