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Record W7066219098

Growth and post-spawning survival in capelin (Mallotus villosus) on the Northeast coast of Newfoundland

2018· dissertation· en· W7066219098 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2018
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsCapelinForage fishSpawn (biology)PredationOtolithPopulation
DOInot available

Abstract

fetched live from OpenAlex

Capelin (Mallotus villosus) is a small, short-lived forage fish species, which is a key prey for many top predators. Newfoundland capelin spawn during the summer, after which most are thought to die. I evaluated the reliability of a spawning zone in the otolith in female capelin by comparing direct (histological) and indirect (otolith-based) indicators of spawning. 50% of individuals with a spawn check identified in the otolith had residual oocytes. This suggests that otolith-based determination may not be a reliable method of identifying previous spawning. I also examined inter-annual variation in growth and links with environmental conditions. Age-specific annual growth was quantified using otolith-based techniques. Generalized Additive Models revealed that higher growth occurred during 2010-2012 and a Principal Components Analysis on environmental factors indicated that these years were characterized by warmer conditions, with earlier and higher magnitude spring blooms, but the abundance of capelin prey varied widely. This suggests that temperature and bloom dynamics may have a larger influence on capelin growth. We highlight the importance of understanding environmental conditions influencing population dynamics, as well as the importance of further characterizing the life history of capelin.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score0.509

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.204
Teacher spread0.195 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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