{"id":"W3093342247","doi":"10.1063/5.0020257","title":"Thomson parabola and time-of-flight detector cross-calibration methodology on the ALLS 100 TW laser-driven ion acceleration beamline","year":2020,"lang":"en","type":"article","venue":"Review of Scientific Instruments","topic":"Laser-Plasma Interactions and Diagnostics","field":"Physics and Astronomy","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut National de la Recherche Scientifique","funders":"H2020 Euratom; Agence Nationale de la Recherche; Compute Canada; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; EUROfusion","keywords":"Beamline; Physics; Optics; Detector; Calibration; Time of flight; Spectrometer; Microchannel plate detector; Joint European Torus; Proton; Nuclear physics; Parabola; Laser; Atomic physics; Beam (structure); Plasma; Tokamak","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004813516,0.0001283686,0.0002774823,0.00004220058,0.0001773848,0.0001029805,0.0001693863,0.000034111,0.00153101],"category_scores_gemma":[0.0001673399,0.00008721749,0.0000914085,0.0002664844,0.0001360809,0.0002424661,0.00006747084,0.0001107676,0.0001140281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001116867,"about_ca_system_score_gemma":0.00004637934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001508904,"about_ca_topic_score_gemma":7.32127e-7,"domain_scores_codex":[0.9987249,0.0001930345,0.0004600543,0.0002711563,0.0002207764,0.0001301175],"domain_scores_gemma":[0.9989198,0.0002804399,0.0003640821,0.0002275522,0.0001440434,0.00006402053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004597764,0.002172854,0.06720118,0.007867632,0.0008308042,0.000003713604,0.002225094,0.001103,0.3545713,0.06233091,0.03674747,0.4644863],"study_design_scores_gemma":[0.0007810502,0.0003853574,0.002315006,0.002677806,0.0001697662,0.000001466501,0.00007777497,0.01765997,0.9361192,0.0009567701,0.03857066,0.0002851803],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996119,0.00008966834,0.0006971593,0.0009878188,0.0004237686,0.0005217363,0.0001375067,0.00000987211,0.001013431],"genre_scores_gemma":[0.9974474,0.0002784201,0.001401169,0.0002897664,0.0001081475,0.00002653919,0.0001710009,0.000009730778,0.0002678478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5815479,"threshold_uncertainty_score":0.9993817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06183515541331907,"score_gpt":0.3309643310630223,"score_spread":0.2691291756497032,"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."}}