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Record W2562673121 · doi:10.1139/cjz-2016-0149

Spring emergence of Eastern Box Turtles (<i>Terrapene carolina</i>): influences of individual variation and scale of temperature correlates

2016· article· en· W2562673121 on OpenAlexvenueno aff
Brett A. DeGregorio, Tracey D. Tuberville, Robert A. Kennamer, Bess B. Harris, I. Lehr Brisbin

Bibliographic record

VenueCanadian Journal of Zoology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsDormancyBiologyTurtle (robot)EcologyHabitatVariation (astronomy)Scale (ratio)AgronomyGeography

Abstract

fetched live from OpenAlex

Many organisms spend considerable time in dormancy to avoid stressful environmental conditions. Understanding the timing and triggers of dormancy behavior is critical for understanding an animal’s life history and behavior. Eastern Box Turtles (Terrapene carolina (L., 1758)) avoid winter temperatures by burrowing into the soil and remaining dormant. Identifying the proximate environmental cues that trigger emergence can improve conservation efforts by reducing potential aboveground turtle mortality. During a 17-year study, half of all variation in emergence timing was attributed to individual variation and the habitat that they occupied during dormancy. We suggest that individual variation in emergence timing is common within populations and confounds efforts to identify reliable emergence cues. Additionally, the scale of meteorological data limits the ability to identify emergence predictors. Using data from temperature loggers placed at dormancy locations, we found that surface air temperatures, averaged over the 5 days prior to emergence, were more strongly related to emergence probability than any variables derived from local weather stations. Turtles generally did not emerge from dormancy until the 5-day mean surface temperatures measured at dormancy sites reached approximately 15 °C. Our results suggest that individuals respond differently to environmental thresholds for emergence and individuals may be characterized as risk-taking or risk-aversive.

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 score0.077
Threshold uncertainty score0.994

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 head0.191
Teacher spread0.183 · 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

Citations21
Published2016
Admission routes1
Has abstractyes

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