{"id":"W2007199116","doi":"10.1016/j.elspec.2013.03.010","title":"Effect of binning on the inversion of ARXPS data","year":2013,"lang":"en","type":"article","venue":"Journal of Electron Spectroscopy and Related Phenomena","topic":"Electron and X-Ray Spectroscopy Techniques","field":"Materials Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Inversion (geology); Synthetic data; Poisson distribution; Regularization (linguistics); Physics; Algorithm; Computational physics; Noise level; Mathematics; Computer science; Geology; Statistics; Artificial intelligence; Acoustics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.004345478,0.0009471708,0.000556555,0.0009932833,0.0009594571,0.001403276,0.0008787794,0.0009637024,0.005921776],"category_scores_gemma":[0.02422979,0.0004765556,0.0002738083,0.001733696,0.00062086,0.001911955,0.001261347,0.001193308,0.0005637444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005637729,"about_ca_system_score_gemma":0.00146777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003839957,"about_ca_topic_score_gemma":0.006715374,"domain_scores_codex":[0.9984092,0.0005784454,0.0002087944,0.0002382527,0.0003253334,0.0002400505],"domain_scores_gemma":[0.98273,0.01219814,0.0005378394,0.001849257,0.002164495,0.0005202355],"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":[0.01819313,0.001251446,0.01524489,0.001206295,0.0004822389,0.0006136681,0.00130449,0.05655127,0.5624152,0.006274768,0.004176562,0.3322861],"study_design_scores_gemma":[0.000196452,0.0008569985,0.02507414,0.0001408913,0.0002500656,0.0005404986,0.0004427702,0.2485028,0.7151337,0.002379435,0.00627458,0.000207768],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8502139,0.00220392,0.1343337,0.0007881026,0.0004622424,0.0001387505,0.001008073,0.006345132,0.004506174],"genre_scores_gemma":[0.9022532,0.0004620604,0.09210424,0.0002941458,0.0000352414,0.00008048149,0.001249767,0.001995969,0.001524949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005921776,"threshold_uncertainty_score":0.02298135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009802817355662229,"score_gpt":0.2730974115269999,"score_spread":0.2632945941713377,"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."}}