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Record W7081569623 · doi:10.48448/ne76-2e17

Assessing Metabolic Rate and Post-tagging Recovery in Juvenile Fish

2025· other· en· W7081569623 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

VenueUnderline Science Inc. · 2025
Typeother
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsDalhousie University
Fundersnot available
KeywordsJuvenileAbiotic componentMetabolic rateFish <Actinopterygii>Juvenile fishFish measurementTroutForage

Abstract

fetched live from OpenAlex

Juvenile fish play a crucial role in the health of aquatic ecosystems, serving both as the lifeline for future generations, but also as a valuable food source for a thriving ecological community. However, these juvenile animals are particularly vulnerable to both biotic and abiotic changes in the ecosystem. Understanding the juvenile life-stage of fish is challenging, because juveniles tend to be small and hard to track, making it hard to gather information about them. As new acoustic tags become smaller and smaller, we are finally being able to shed light into understudied life-stages, including juvenile fish, forage fishes, and even baitfishes. But tagging such small animals can introduce sub-lethal effects that alter their physiology and behaviour, ultimately biasing the collected data and any subsequent analyses and conclusions. Here, we tested if tagging juvenile brook trout (Salvelinus fontinalis) of two size classes (10-12 cm and 13-16 cm fork length) with a 417 kHz LOTEK PinTag induced changes in their oxygen consumption rates (ṀO2 ) immediately after tagging and over a period of two days. Findings will help to guide new research on small fish and open telemetry towards previously intractable species and size classes.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.775
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.015
GPT teacher head0.268
Teacher spread0.253 · 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