{"id":"W2793580455","doi":"10.1016/j.jenvrad.2018.01.026","title":"Airborne gamma-ray spectra processing: Extracting photopeaks","year":2018,"lang":"en","type":"article","venue":"Journal of Environmental Radioactivity","topic":"Radioactivity and Radon Measurements","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Maple Leaf Foods","funders":"","keywords":"Spectral line; Spectrometer; Energy (signal processing); Noise (video); Resolution (logic); SIGNAL (programming language); Physics; Computer science; Optics; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00243641,0.0003167746,0.0005952507,0.0002012762,0.001119731,0.00002649974,0.0003677787,0.0002581693,0.001911616],"category_scores_gemma":[0.0002145909,0.0002663916,0.0002319999,0.0001802355,0.0003706605,0.001249074,0.00007818274,0.001748507,0.0002621416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001112868,"about_ca_system_score_gemma":0.0002739681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002373004,"about_ca_topic_score_gemma":0.00001932812,"domain_scores_codex":[0.9963341,0.0007263254,0.0009456317,0.0003392491,0.0009436653,0.000711012],"domain_scores_gemma":[0.9972981,0.0003248333,0.001596906,0.0003408092,0.00005854075,0.00038085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001529924,0.002368745,0.1623099,0.0001641548,0.0003750925,0.0002335419,0.005157558,0.00003167152,0.7033816,0.00002739866,0.004758811,0.1196616],"study_design_scores_gemma":[0.00371054,0.001081739,0.896363,0.0004823649,0.0002122446,0.0003540402,0.003212325,0.000302794,0.03231472,0.0001482559,0.06122349,0.0005944603],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829391,0.0004415051,0.00321181,0.0004868429,0.001470822,0.0004102426,0.00001594393,0.00003504126,0.01098868],"genre_scores_gemma":[0.9933784,0.0001792473,0.002467636,0.0003420666,0.002727844,0.000008032824,0.00000153159,0.00005536555,0.0008398523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7340532,"threshold_uncertainty_score":0.9999788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04904872043496444,"score_gpt":0.3553096807979668,"score_spread":0.3062609603630023,"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."}}