{"id":"W2808901927","doi":"10.1038/s41598-018-27714-5","title":"Recovery of Degraded-Beyond-Recognition 19th Century Daguerreotypes with Rapid High Dynamic Range Elemental X-ray Fluorescence Imaging of Mercury L Emission","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Cultural Heritage Materials Analysis","field":"Arts and Humanities","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Museum of Fine Arts of Quebec; Canadian Light Source (Canada); Western University","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Division of Materials Research; Canada Research Chairs; National Science Foundation; National Institutes of Health; University of Saskatchewan; Canadian Light Source","keywords":"Mercury (programming language); Materials science; Synchrotron; Specular reflection; Copper; Optics; Computer science; Metallurgy; Physics","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":[0.0001833895,0.0002699389,0.000155361,0.0008998454,0.0003130584,0.0007724488,0.0003079062,0.0005398346,0.002762055],"category_scores_gemma":[0.0004999964,0.0002041537,0.0001834934,0.0004046784,0.0004168828,0.0003581279,0.0004312544,0.0005314362,0.001374854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004480189,"about_ca_system_score_gemma":0.0002697025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002091544,"about_ca_topic_score_gemma":0.006156241,"domain_scores_codex":[0.9998616,0.000009330898,0.000004942218,0.00003645381,0.00005401811,0.00003368187],"domain_scores_gemma":[0.9997793,0.00002910311,0.00003982038,0.00005953886,0.00007330098,0.00001902853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000100208,0.00001413048,0.00276308,0.00009114894,0.00001076828,0.0005554898,0.0003628422,0.0002998537,0.9632961,0.0008566747,0.000880782,0.0307689],"study_design_scores_gemma":[0.00000554565,0.00007043144,0.03100702,0.00003370024,0.00002062512,0.001909241,0.0003959845,0.001623837,0.9334605,0.0002669591,0.03117805,0.00002813275],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9094026,0.001420209,0.06618098,0.0003915378,0.0001767446,0.00006404569,0.001172785,0.001002997,0.0201881],"genre_scores_gemma":[0.8994079,0.0009139944,0.07154912,0.0001835381,0.0000235294,0.00002837576,0.0008705408,0.0004841218,0.02653909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002762055,"threshold_uncertainty_score":0.009239972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01362266917019373,"score_gpt":0.2165172270643529,"score_spread":0.2028945578941592,"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."}}