{"id":"W2013997163","doi":"10.7567/jjap.53.05fh01","title":"Optimization of the design of a multilayer X-ray mirror for Cu-Kα energy","year":2014,"lang":"en","type":"article","venue":"Japanese Journal of Applied Physics","topic":"Advanced X-ray Imaging Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Atomic Energy (Canada); Canadian Nuclear Laboratories","funders":"","keywords":"Optics; Reflectivity; Energy (signal processing); Materials science; Quarter (Canadian coin); Layer (electronics); Line (geometry); X-ray; Optoelectronics; Physics; Nanotechnology; Mathematics; Geometry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004003272,0.0008201223,0.0004796519,0.0003772592,0.000255632,0.0006094063,0.0006237595,0.0004245469,0.0009150996],"category_scores_gemma":[0.0006199949,0.0004514091,0.0004588292,0.0002465124,0.0001800642,0.0004568841,0.0002652419,0.0003444781,0.0004678997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006376858,"about_ca_system_score_gemma":0.000680916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006802716,"about_ca_topic_score_gemma":0.0009689628,"domain_scores_codex":[0.9997237,0.00002592923,0.00002306508,0.00005308844,0.0001349286,0.00003919703],"domain_scores_gemma":[0.9996821,0.00003915083,0.0001026913,0.00004604054,0.0001079688,0.00002209365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001066854,0.00004317996,0.00110382,0.0003218386,0.00004549401,0.0001118262,0.00007408679,0.01688304,0.9588341,0.001796481,0.0004091752,0.02027039],"study_design_scores_gemma":[0.00007603443,0.0007697997,0.00482981,0.00004415126,0.0001230923,0.0006298993,0.00008719552,0.1407843,0.8368847,0.0005181733,0.01518035,0.00007241251],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4375311,0.001896943,0.5490552,0.0002213614,0.0001787099,0.0003659573,0.0003618594,0.001197271,0.009191636],"genre_scores_gemma":[0.5298733,0.0005446023,0.4667166,0.0000267239,0.00001656268,0.0002400189,0.0001795215,0.0001370847,0.002265643],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009150996,"threshold_uncertainty_score":0.004626691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.014740574270196,"score_gpt":0.2517255552267051,"score_spread":0.2369849809565091,"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."}}