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Record W2282194351 · doi:10.3109/1354750x.2016.1139183

XRF-measured bone lead (Pb) as a biomarker for Pb exposure and toxicity among children diagnosed with Pb poisoning

2016· article· en· W2282194351 on OpenAlexaff
Aaron J. Specht, Yanfen Lin, Marc G. Weisskopf, Chonghuai Yan, Howard Hu, Jian Xu, Linda H. Nie

Bibliographic record

VenueBiomarkers · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersNational Institute for Occupational Safety and HealthNational Institute of Environmental Health Sciences
KeywordsBiomarkerLead poisoningToxicityMedicineLead exposureEnvironmental chemistryNuclear medicineInternal medicineChemistry

Abstract

fetched live from OpenAlex

Childhood lead (Pb) poisoning remains a global issue, especially in industrial areas. In this study, 115 children with average age 5.7 years were recruited as either patient diagnosed with Pb poisoning or controls at Xinhua Hospital in China. The subjects' bone Pb was measured with a K-shell X-ray fluorescence (KXRF) and a portable X-ray fluorescence (XRF) system. A significant correlation between KXRF bone Pb and blood Pb and portable XRF and KXRF measurements were observed. The half-life of blood-lead was calculated to be 9.96 ± 3.92 d. Our results indicate that bone is a useful biomarker for Pb in children.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.221
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations71
Published2016
Admission routes1
Has abstractyes

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