{"id":"W2592753372","doi":"10.1088/1361-6579/aa63d3","title":"Calibration of the <sup>125</sup> I-induced x-ray fluorescence spectrometry-based system of <i>in vivo</i> bone strontium determinations using hydroxyapatite as a phantom material: a simulation study","year":2017,"lang":"en","type":"article","venue":"Physiological Measurement","topic":"X-ray Spectroscopy and Fluorescence Analysis","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Imaging phantom; Strontium; Calibration; Materials science; Monte Carlo method; Biomedical engineering; Normalization (sociology); Analytical Chemistry (journal); Chemistry; Optics; Physics; Mathematics; Medicine; Nuclear physics; Chromatography","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":[0.0005776049,0.0002404452,0.000546049,0.0001101809,0.0003192827,0.00007632806,0.0004658098,0.00005685147,0.00008934468],"category_scores_gemma":[0.00006706789,0.0001694233,0.0002233086,0.0002655136,0.0001077996,0.0002316262,0.0001008169,0.0001397063,0.000001545675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001452918,"about_ca_system_score_gemma":0.00009757568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001226293,"about_ca_topic_score_gemma":0.00002715271,"domain_scores_codex":[0.9976248,0.0003200671,0.0006501554,0.0003987944,0.0007144345,0.0002917767],"domain_scores_gemma":[0.9981925,0.00004138768,0.0007409314,0.0007489037,0.0002204035,0.00005589992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009308871,0.0009812117,0.0272476,0.00004167589,0.00007437843,0.000001042167,0.0001506599,0.08975334,0.8812379,0.0002837941,0.000001541566,0.0001337749],"study_design_scores_gemma":[0.0009064504,0.0003796013,0.09091215,0.0002350815,0.0001768169,9.94393e-8,0.0004979661,0.5611587,0.3453348,0.0002014777,5.557098e-7,0.0001962274],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917114,0.000005895855,0.007196705,0.00002495862,0.00007255221,0.0008454965,0.00003932095,0.00001735739,0.00008627784],"genre_scores_gemma":[0.9991162,2.820179e-7,0.0006834398,0.000005279022,0.000120239,0.0000529406,0.000005824998,0.00001314896,0.000002692237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.535903,"threshold_uncertainty_score":0.690888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04862192380068363,"score_gpt":0.2997294644979273,"score_spread":0.2511075406972437,"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."}}