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The Overwintering Strategy of Hatchling Painted Turtles, or How to Survive in the Cold without Freezing

2001· article· en· W2272471411 on OpenAlexaboutno aff
Gary C. Packard, Mary J. Packard

Bibliographic record

VenueBioScience · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsHatchlingOverwinteringPainted turtleBiologyZoologyEcologyFisheryTurtle (robot)

Abstract

fetched live from OpenAlex

Painted turtles (Chrysemys picta) are common residents of shallow lakes and marshes across much of North America east of the Rocky Mountains—so common, in fact, that the species has become a “model organism” for studies on the ecology and evolution of chelonians (Wilbur and Morin 1988). The natural history of painted turtles differs from that of most other species in an important respect, however. Whereas neonates of other freshwater turtles usually emerge from their subterranean nest in late summer or autumn and move to a nearby marsh, lake, or stream to spend their first winter, hatchling painted turtles typically remain inside their shallow (8–14 cm) nest throughout their first winter and do not emerge above the ground until the following spring (Ernst et al. 1994). This behavior commonly causes neonatal painted turtles in northern regions—from Nebraska (Packard 1997, Packard et al. 1997a), northern Illinois (Weisrock and Janzen 1999), and New Jersey (DePari 1996) northward to the limit of distribution in southern Canada (Storey et al. 1988)—to be exposed during winter to ice and cold, with temperatures in some nests dipping below –10°C (Figure 1). Many of these hatchlings withstand such extremes and emerge from the nest when the soil finally thaws in the spring (Table 1).

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.033
GPT teacher head0.255
Teacher spread0.222 · 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 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

Citations19
Published2001
Admission routes1
Has abstractyes

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