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Record W2083620413 · doi:10.1577/h03-083.1

A Method for Measuring Total Thiaminase Activity in Fish Tissues

2005· article· en· W2083620413 on OpenAlexaff
James L. Zajicek, Donald E. Tillitt, Dale C. Honeyfield, Scott Brown, John D. Fitzsimons

Bibliographic record

VenueJournal of Aquatic Animal Health · 2005
Typearticle
Languageen
FieldMedicine
TopicBiochemical effects in animals
Canadian institutionsFisheries and Oceans CanadaEnvironment and Climate Change Canada
FundersGreat Lakes Fishery Trust
KeywordsBiologyFish <Actinopterygii>ZoologyFishery

Abstract

fetched live from OpenAlex

Abstract An accurate, quantitative, and rapid method for the measurement of thiaminase activity in fish samples is required to provide sufficient information to characterize the role of dietary thiaminase in the onset of thiamine deficiency in Great Lakes salmonines. A radiometric method that uses 14C-thiamine was optimized for substrate and co-substrate (nicotinic acid) concentrations, incubation time, and sample dilution. Total thiaminase activity was successfully determined in extracts of selected Great Lakes fishes and invertebrates. Samples included whole-body and selected tissues of forage fishes. Positive control material prepared from frozen alewives Alosa pseudoharengus collected in Lake Michigan enhanced the development and application of the method. The method allowed improved discrimination of thiaminolytic activity among forage fish species and their tissues. The temperature dependence of the thiaminase activity observed in crude extracts of Lake Michigan alewives followed a Q10 = 2 relationship for the 1–37°C temperature range, which is consistent with the bacterial-derived thiaminase I protein.

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)0.001
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: none
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.004

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 head0.054
GPT teacher head0.404
Teacher spread0.350 · 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

Citations47
Published2005
Admission routes1
Has abstractyes

Explore more

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