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Record W4311681168 · doi:10.22215/etd/2022-15293

The overwintering behaviour and physiology of Northern map turtles (Graptemys geographica) in Ontario

2022· dissertation· en· W4311681168 on OpenAlexaffabout
Jessica Robichaud

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsCarleton University
Fundersnot available
KeywordsOverwinteringRespirometryJuvenileEcologyBiologyZoology

Abstract

fetched live from OpenAlex

Northern map turtles (Graptemys geographica) are a freshwater turtle species that spends months of the year overwintering submerged under ice.They are anoxia intolerant, making their ability to survive submerged without access to atmospheric oxygen physiologically impressive.Overwintering behaviour and physiology were examined to understand how this species survives the winter.Biologgers recorded locomotor activity, temperature, and depth throughout overwintering.Locomotor activity was continuous during the winter.The amount of movement differed between adult females, juvenile females, and adult males.Temperature preference for all groups was near 1°C and each moved progressively shallower as winter progressed.Respirometry was used to measure adult female standard metabolic rates at under-ice temperatures.Metabolism was lower at lower temperatures (i.e., 1°C versus 4°C), indicating considerable metabolic savings at 1°C.The behaviours observed likely reflect this species working to meet winter oxygen and energetic needs which differ based on size specific physiological needs.Bulté in particular for teaching me innumerable practical field skills and for his patience during our long excursions on the water.My appreciation extends to the members of the Cooke and MacMillan labs as well who created a friendly working environment and were always keen to offer their support virtually and in the field.I'd also like to thank the Queen's University Biology station for allowing me to use their research facilities to complete both projects associated with my data chapters.Finally, I would like to thank my family and my friends for the endless support and encouragement as I continue to pursue my academic endeavors.I am grateful for the opportunities and experiences I was fortunate enough to have during my time at Carleton University and look forward to carrying these with me into the future.

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 score0.358
Threshold uncertainty score0.721

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 studies0.0010.000
Scholarly communication0.0000.000
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 head0.008
GPT teacher head0.211
Teacher spread0.202 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

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