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Record W4400126135 · doi:10.53607/wrb.v42.269

Reproducibility of blood lead levels after blood stored for seven days in trumpeter swans (Cygnus buccinator) and mute swans (Cygnus olor)

2024· article· en· W4400126135 on OpenAlexaff
Sherri Cox

Bibliographic record

VenueWildlife Rehabilitation Bulletin · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsReproducibilityBiologyMathematics

Abstract

fetched live from OpenAlex

Wild animals, particularly birds, often present with clinical signs of lead toxicosis when admitted to wildlife rehabilitation centers. Many wildlife rehabilitators and wildlife biologists do not have a point-of-care blood lead level analyzer, nor do they always have the financial resources to submit samples for external laboratory analyses. Often there is a delay between taking a blood sample in the field and subsequent analysis. The objective of this study was to determine whether a delay in processing a blood sample for lead testing would significantly alter the blood lead level results in swans. Whole blood samples were collected from 49 trumpeter swans and four mute swans and placed in ethylenediaminetetraacetic acid (EDTA) blood collection tubes. Samples were run on a LeadCare II analyzer at day 0, stored at 4°C for 7 days, and rerun on day 7. Results indicate that whole blood can be stored in EDTA blood collection tubes for up to seven days at 4°C while maintaining reproducibility in blood lead level results that were analyzed from a point-of-care blood lead level system.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.259
Teacher spread0.246 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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