MétaCan
Menu
Back to cohort
Record W198293276

First AID (Atom counting for Isotopic Determination).

2002· paratext· en· W198293276 on OpenAlexaff
Jeffrey L. Roach, Kimberly M. Israel, R. E. Steiner, C.J. Duffy, Fred R. Roench

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2002
Typeparatext
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsKimberly-Clark (Canada)
Fundersnot available
KeywordsAtom (system on chip)Computer scienceEmbedded system
DOInot available

Abstract

fetched live from OpenAlex

Los Alamos National Laboratory (LANL) has established an in vitro bioassay monitoring program in compliance with the requirements in the Code of Federal Regulations, 10 CFR 835, Occupational Radiation Protection. One aspect of this program involves monitoring plutonium levels in at-risk workers. High-risk workers are monitored using the ultra-sensitive Therrnal Ionization Mass Spectrometry (TIMS) technique to ensure compliance with DOE standards. TIMS is used to measure atom ratios of 239Pua nd 240Puw ith respect to a tracer isotope ('Pu). These ratios are then used to calculate the amount of 239Pu and 240Pup resent. This low-level atom counting technique allows the calculation of the concentration levels of 239Pu and 240Pu in urine for at risk workers. From these concentration levels, dose assessments can be made and worker exposure levels can be monitored. Detection limits for TIMS analysis are on the order of millions of atoms, which translates to activity levels of 150 aCi 239Pua nd 500 aCi for 240Pu. pCi for Our poster presentation will discuss the ultra-sensitive, low-level analytical technique used to measure plutonium isotopes and the data verification methods used for validating isotopic measurements.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.225
Teacher spread0.214 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)Same topicRadioactive contamination and transferFrench-language works237,207