{"id":"W3085703604","doi":"10.1107/s1600577520010838","title":"<i>X-ray Spectral Imaging Program: XSIP</i>","year":2020,"lang":"en","type":"article","venue":"Journal of Synchrotron Radiation","topic":"Advanced X-ray and CT Imaging","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Western Economic Diversification Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Research Council Canada; Canada Foundation for Innovation; University of Saskatchewan; Canadian Light Source","keywords":"Monochromator; Synchrotron radiation; Software; Python (programming language); Workflow; Synchrotron; Computer science; Optics; Imaging spectroscopy; Image processing; Data processing; Spectral imaging; Computational science; Physics; Computer graphics (images); Artificial intelligence; Hyperspectral imaging; Database","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":[],"consensus_categories":[],"category_scores_codex":[0.000111849,0.0001255116,0.000186854,0.00007427705,0.0000422904,0.00005410756,0.0001275756,0.00002726458,0.00004293719],"category_scores_gemma":[0.00003714638,0.0001228696,0.0001029296,0.0001882449,0.00001847052,0.0006771109,0.000008029634,0.0002985134,0.0000226853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001067106,"about_ca_system_score_gemma":0.00002742831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.033037e-7,"about_ca_topic_score_gemma":2.152378e-7,"domain_scores_codex":[0.9990823,0.00001795545,0.000389388,0.00008120793,0.0002133809,0.0002158192],"domain_scores_gemma":[0.9995612,0.0000217793,0.000150141,0.00006574603,0.00005179915,0.0001493349],"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":[0.0000634052,0.00006643684,0.006277285,0.0001481927,0.0001137599,0.00009418985,0.001727228,0.3949612,0.0859082,0.0001918599,0.005469832,0.5049784],"study_design_scores_gemma":[0.004100606,0.0006716223,0.0261201,0.0002453514,0.0002214254,0.0002885937,0.001106644,0.7820719,0.05230724,0.0009350097,0.1309073,0.001024186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6145577,0.009755554,0.3618017,0.005564172,0.001901956,0.0006229163,0.00000843128,0.000763514,0.005023962],"genre_scores_gemma":[0.988133,0.0001507719,0.01037765,0.0002053134,0.001092417,0.000003759284,0.000002421599,0.00002985519,0.000004861506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5039542,"threshold_uncertainty_score":0.5010477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005524496189211959,"score_gpt":0.2185927376949345,"score_spread":0.2130682415057225,"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."}}