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Record W4254442402 · doi:10.1079/9781786393982.0163

Ionic regulation.

2019· book-chapter· en· W4254442402 on OpenAlexaff
Jonathan M. Wilson, Pedro M. Guerreiro

Bibliographic record

VenueCABI eBooks · 2019
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsFish <Actinopterygii>Climate changeBiologyOcean acidificationEcologyFishery

Abstract

fetched live from OpenAlex

In this chapter the effect of climate change on ionoregulation in fishes was discussed. Ionoregulation in fishes is essential for survival and success, and osmoregulatory failure is often observed as a precursor to death. The two main climate change factors that are considered in this chapter are: (i)temperature; and (ii) Carbon dioxide-induced acidification. Also presented in this chapter are reviews of the basic mechanisms of ion regulation in marine and freshwater fishes, acid-base regulation, and their links. Studies on the predicted impacts of higher temperatures and aquatic hypercapnia on ion regulation in fishes were reviewed. In the final part of the chapter the side effects of acid-base regulation on otolith growth and GABAA (γ-aminobutyric acid, type A) receptor-associated behavioural changes were discussed. The chapter ends with some future directions in climate-change-associated research into ion regulation in fishes. Although there is consensus that these changes are occurring; predicting long-term impacts on fish populations is still a work in progress.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.101
Threshold uncertainty score0.338

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.1010.083

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 head0.021
GPT teacher head0.195
Teacher spread0.174 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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