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Record W7100050245

Food for Thought Death from near and far: alternate perspectives on size-dependent

2015· article· en· W7100050245 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Ecology and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPlanktivoreTable (database)Trophic levelFish <Actinopterygii>LarvaZooplankton
DOInot available

Abstract

fetched live from OpenAlex

This essay contrasts the inferences about the patterns of size-dependentmortality in larval fish based on the traditional catch-curve approachwith that achieved through the vertical life table method in an application to data from coastal Newfoundland. Although both approaches reveal that the average mortality rates decline with increasing body size, the rate of decline estimated using the vertical life table approach is much less pro-nounced than estimated from the catch-curvemethod.More important, however, is that on a case-by-case assessment the vertical life table reveals that mortality increases with increasing body size in 70 % of the cases and declines in the remainder. Instances with greater rates of loss in larger individuals are consistent with larvae becomingmore susceptible to the dominant planktivore in the study region. The contrasting results indicate that the patterns of change inmortality rates need to bemeasured over relatively short-time and/or length intervals. Such inferences have import-ant implications for the development of studies dealing with larval fish dynamics. To be effective and applicable, comparative analyses that aim to developmacroscopic principles for the early life stages of fishmust take the local foodweb structure into consideration to gain appropriate under-standing of the trophic interactions that most strongly affect losses from larval fish populations.

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 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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.136

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.055
GPT teacher head0.234
Teacher spread0.179 · 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 teacher head, 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
Published2015
Admission routes1
Has abstractyes

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