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Record W7135094664 · doi:10.5376/ijmec.2024.14.0029

Gene-Environment Interactions in Amphipods: Implications for Evolution and Conservation

2024· article· W7135094664 on OpenAlexvenueno aff
Fangqi Xu

Bibliographic record

VenueInternational Journal of Molecular Ecology and Conservation · 2024
Typearticle
Language
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsGammarusAdaptation (eye)EcosystemMechanism (biology)Environmental changeFreshwater ecosystem

Abstract

fetched live from OpenAlex

Gammarus gammarus is widely distributed in freshwater, brackish water and coastal ecosystems and is an important model group for studying the adaptive evolution of organisms. Gene-environment interaction (G×E) is of key significance in the evolution and ecological protection of gammarus. This study summarizes the adaptive patterns of gammarus populations in different ecological environments and explores the latest progress of G×E research in revealing the ecological adaptation and evolution mechanisms of gammarus. The study found that the gene expression responses of gammarus to environmental stresses such as temperature, salinity and pollutants are significantly environmentally specific, and genomics and epigenetic mechanisms play a core role in the adaptive evolution of gammarus. Typical cases show that the response of freshwater gammarus populations to temperature gradients, the salt tolerance mechanism of marine gammarus, and the adaptive evolution under pollution stress all show obvious G×E patterns. Future research should focus on solving the technical bottlenecks of G×E research, strengthening multidisciplinary cross-integration and long-term ecological monitoring, so as to achieve the goal of protecting gammarus populations and managing ecosystem health. G×E research on gammarus not only deepens the understanding of adaptive evolution theory, but also provides important methods and data support for species risk assessment, ecological monitoring and ecological restoration.

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)0.001
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 score0.116
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.019
GPT teacher head0.283
Teacher spread0.264 · 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
Published2024
Admission routes1
Has abstractyes

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