MétaCan
Menu
Back to cohort
Record W2092633508 · doi:10.1088/0031-9155/55/6/n02

Simultaneous assessment of arsenic and selenium in human nail phantoms using a portable x-ray tube and a detector

2010· article· en· W2092633508 on OpenAlexafffund
Christopher Roy, Mihai R. Gherase, David Fleming

Bibliographic record

VenuePhysics in Medicine and Biology · 2010
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsMount Allison University
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsArsenicSeleniumNail (fastener)Materials scienceTube (container)Nuclear medicineRadiochemistryChemistryComposite materialMedicineMetallurgy

Abstract

fetched live from OpenAlex

A novel approach to the measurement of arsenic and selenium in nail phantoms is demonstrated. Two-component nail phantoms of 0.7 mm and 1.5 mm thickness were made from a polyester resin-salt mixture and dosed with equal arsenic and selenium concentrations ranging from 0 to 30 microg g(-1). A backing was made to simulate the soft tissue and bone of the great toe. Characteristic x-rays for arsenic and selenium were recorded using a portable x-ray tube and a silicon PiN diode detector. The minimum instrumental detection limits for arsenic and selenium in 0.7 mm solitary nail samples were as follows: 0.510 +/- 0.018 microg g(-1) and 0.519 +/- 0.026 microg g(-1) respectively; for 1.5 mm solitary nail: 0.465 +/- 0.035 microg g(-1) and 0.561 +/- 0.062 microg g(-1); for 0.7 mm nail with backing: 1.522 +/- 0.038 microg g(-1) and 1.401 +/- 0.049 microg g(-1); for 1.5 mm nail with backing: 1.354 +/- 0.054 microg g(-1) and 1.367 +/- 0.068 microg g(-1).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.093
GPT teacher head0.416
Teacher spread0.322 · 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 designBench or experimental
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

Citations27
Published2010
Admission routes2
Has abstractyes

Explore more

Same venuePhysics in Medicine and BiologySame topicRadiation Dose and ImagingFrench-language works237,207