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Scalable Dialysis-Based Method for the Isolation of Strontium from Milk for Radioanalysis

2023· article· en· W4383895775 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACS Food Science & Technology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsAgriculture and Agri-Food CanadaHealth Canada
Fundersnot available
KeywordsStrontiumChromatographyStrontium-90Certified reference materialsChemistryMaterials scienceDetection limitRadionuclideOrganic chemistry

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide An ashless dialysis-based method for the convenient and timely removal of strontium from milk for radioanalysis has been described for samples ranging from 100 to 500 mL following a brief (30 min) treatment with formaldehyde solution. Overall strontium recovery is suitably high and remarkably consistent across all sample sizes (81–84%), with the final isolation of strontium from milk comfortably achieved within 32 h. For strontium carrier quantification and quality assurance purposes, two chromatographic high-pressure ion chromatography methods were developed to fully resolve strontium from the cationic mineral constituents of milk, as well as yttrium, while method validation was performed with a certified reference material (IAEA-152 milk powder) containing strontium-90. This methodology is highly amenable to concurrent multisample processing which, considering its scalability, makes it well-suited to environmental surveillance of radiostrontium in milk for both routine and emergency response applications.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.799
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.278
Teacher spread0.261 · 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