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Effects of food abundance on genetic and maternal variation in the growth rate of juvenile red squirrels

2003· article· en· W2088488245 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Evolutionary Biology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyJuvenileGenetic variationMaternal effectAbundance (ecology)Variation (astronomy)Adaptation (eye)Quantitative geneticsOffspringNatural selectionSelection (genetic algorithm)CovariancePopulationEcologyZoologyDemographyStatisticsGenetics

Abstract

fetched live from OpenAlex

Sources of variation in growth in body mass were assessed in natural and experimental conditions of high and low food abundance using reciprocal cross-fostering techniques and long-term data (1987-2002) for a population of North American red squirrels (Tamiasciurus hudsonicus). Growth rates were significantly higher in naturally good and food supplemented conditions, than in poor conditions. Mother-offspring resemblance was higher in poor conditions as a result of large increases in both the direct genetic variance and direct-maternal genetic covariance and a smaller increase in the coefficient of maternal variation. Furthermore, the genetic correlation across environments was significantly less than one indicating that sources of heritable variation differed between the two environments. These results are consistent with the hypothesis that selection has eroded heritable variation for growth more in good conditions and indicate the potential for independent adaptation of growth rates in good and poor conditions.

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)0.000
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 score0.083
Threshold uncertainty score0.139

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 head0.007
GPT teacher head0.219
Teacher spread0.212 · 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