{"id":"W4297846629","doi":"10.21203/rs.3.rs-1407116/v1","title":"A spatial beam property analyzer based on dispersive crystal diffraction for low-emittance X-ray light sources","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced X-ray Imaging Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Basic Energy Sciences; Natural Sciences and Engineering Research Council of Canada; University of Saskatchewan; Paul Scherrer Institut; U.S. Department of Energy","keywords":"Monochromator; Optics; Beamline; Wiggler; Diffraction; Thermal emittance; Synchrotron; Beam (structure); Beam divergence; Synchrotron radiation; Crystal (programming language); Characterization (materials science); Advanced Photon Source; Materials science; Synchrotron Radiation Source; Laser beam quality; Physics; Laser; Cathode ray; Electron; Computer science","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","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008250976,0.0004476934,0.0004997387,0.0004730783,0.0007268898,0.0002409121,0.0007874331,0.0001419236,0.001022182],"category_scores_gemma":[0.0001738239,0.0003528272,0.0004468787,0.0003382275,0.0001622726,0.0001614912,0.0008401832,0.002336951,0.00001678371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005920358,"about_ca_system_score_gemma":0.0004966165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001011526,"about_ca_topic_score_gemma":0.00001968635,"domain_scores_codex":[0.995972,0.0003632973,0.0003781712,0.001161249,0.001280449,0.0008447948],"domain_scores_gemma":[0.9973411,0.0005026826,0.0002623328,0.001113259,0.0005926344,0.0001879953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01040757,0.01537086,0.228512,0.01120141,0.002334384,0.0001903508,0.008308467,0.3295689,0.0629853,0.005018037,0.1299018,0.1962009],"study_design_scores_gemma":[0.005011023,0.003497213,0.01294703,0.00542918,0.0002672594,0.000001200397,0.006429041,0.2755824,0.06506234,0.0295639,0.5918559,0.004353467],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1261841,0.0003368555,0.8357679,0.005990133,0.0009004374,0.01432103,0.004265684,0.0009049035,0.01132894],"genre_scores_gemma":[0.9872909,0.000009489538,0.004179487,0.00004196479,0.001075767,0.004262591,0.001090875,0.0001275619,0.001921391],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8611068,"threshold_uncertainty_score":0.9999647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02709128368165549,"score_gpt":0.3604075724580511,"score_spread":0.3333162887763956,"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."}}