{"id":"W3205153614","doi":"10.1002/xrs.3271","title":"Quantification of gold nanoparticles in histologically thin tissue slices using <scp>TXRF</scp>","year":2021,"lang":"en","type":"article","venue":"X-Ray Spectrometry","topic":"MRI in cancer diagnosis","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Colloidal gold; Materials science; Fluorescence; Nanoparticle; Sample preparation; Scanning electron microscope; Analytical Chemistry (journal); Chemistry; Nanotechnology; Chromatography; Optics","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":[0.0003896163,0.0001661812,0.000490598,0.0003161262,0.00003155475,0.00002324827,0.0001580679,0.0001473874,0.0003287164],"category_scores_gemma":[0.001144099,0.0001600816,0.00008355305,0.001431158,0.0001061941,0.0001088166,0.00005994535,0.0002476466,0.0000375005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002894895,"about_ca_system_score_gemma":0.0001729627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001400032,"about_ca_topic_score_gemma":0.00009616634,"domain_scores_codex":[0.9981937,0.00008852088,0.0005270907,0.0004476901,0.0004028075,0.0003401862],"domain_scores_gemma":[0.9983274,0.0006857168,0.0002147507,0.0005172344,0.0001473684,0.0001075206],"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":[0.00001013212,0.0005469847,0.09594341,0.0001593202,0.00003198474,0.0001184696,0.0003172492,0.00007946481,0.8992286,0.0006173635,0.002411645,0.0005353506],"study_design_scores_gemma":[0.0006505603,0.0002537199,0.1721559,0.0001956281,0.00009350989,0.0000478503,0.0006393583,0.0004280775,0.81694,0.0002907892,0.008230017,0.00007456283],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900663,0.004613949,0.0002551286,0.001526565,0.0002196135,0.0002338332,0.00001145146,0.00006117743,0.003011955],"genre_scores_gemma":[0.976127,0.0008108165,0.02194396,0.0002512501,0.0001239957,0.00001732482,0.00001621023,0.00002569904,0.0006837068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08228862,"threshold_uncertainty_score":0.6527938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0441330787253717,"score_gpt":0.3192699624691049,"score_spread":0.2751368837437332,"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."}}