{"id":"W1971171684","doi":"10.1007/s10967-008-0610-1","title":"Linssi: Database for gamma-ray spectrometry","year":2008,"lang":"en","type":"article","venue":"Journal of Radioanalytical and Nuclear Chemistry","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Canada","funders":"","keywords":"Gamma ray spectrometry; Sample (material); Calibration; Database; Computer science; Semiconductor detector; Sampling (signal processing); Detector; Physics; Chemistry; Radiochemistry; Chromatography","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":[0.001514168,0.003775758,0.002824876,0.008923732,0.0008013093,0.002723469,0.005513404,0.002964783,0.04936824],"category_scores_gemma":[0.006136018,0.001222181,0.001704804,0.01061007,0.0005106243,0.003181384,0.002627272,0.001835497,0.07496969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001426081,"about_ca_system_score_gemma":0.002663327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004293468,"about_ca_topic_score_gemma":0.003138718,"domain_scores_codex":[0.998838,0.0001495818,0.0002451006,0.0002260575,0.0003953906,0.000145834],"domain_scores_gemma":[0.9966363,0.0005893382,0.0003945563,0.001311752,0.000823588,0.0002445234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001814404,0.0001969312,0.006357349,0.004533619,0.0005059972,0.0005097234,0.0001469377,0.007144144,0.01676887,0.006722673,0.859332,0.09596743],"study_design_scores_gemma":[0.0004762255,0.0001027603,0.003873186,0.0003412707,0.0003218756,0.0006890274,0.00006577489,0.01275638,0.0222116,0.01070189,0.9482622,0.0001978098],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.003764313,0.002393061,0.03449346,0.0002937696,0.000153368,0.0001708853,0.7964949,0.1520772,0.01015902],"genre_scores_gemma":[0.01052787,0.001269251,0.02628391,0.0002563965,0.00006307758,0.0003394486,0.9512041,0.007746763,0.002309263],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04936824,"threshold_uncertainty_score":0.1651532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01131164736371332,"score_gpt":0.2330826595870978,"score_spread":0.2217710122233845,"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."}}