MétaCan
Menu
Back to cohort
Record W7067286731

Local and regional scale habitat selection by wood turtles (Glyptemys Insculpta) in Ontario

2006· dissertation· en· W7067286731 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2006
Typedissertation
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsHabitatRiparian zoneTurtle (robot)ForagingScale (ratio)Selection (genetic algorithm)Logistic regressionGeneralized additive modelRegression analysis
DOInot available

Abstract

fetched live from OpenAlex

This study investigated the distribution of Wood Turtle populations at the regional scale and habitat selection by individuals at the local scale. The studies at both scales were guided by 'a priori' knowledge of the importance of thermoregulation, nesting, hibernation and foraging to Wood Turtles. At the regional scale, data were collected from eight stream reaches inhabited by Wood Turtles and 52 non-inhabited reaches. Models were fitted to the data using logistic regression and evaluated for fit, significance of parameter estimates, and predictive success. Results indicated that Wood Turtles are "stream specialists", occurring along stream reaches with available nesting sites, hibernacula, and diverse riparian habitats. At the local-scale, 260 radio-telemetry locations were obtained from 20 Wood Turtles, pre- and post-nesting; habitat characteristics were measured at these locations, and at 260 random locations, each associated with a turtle location. Models were fitted to the data using conditional logistic regression and evaluated for fit, significance of parameter estimates, and predictive success. Results indicated that Wood Turtles are "habitat specialists" pre- and post-nesting, selecting terrestrial habitats close to the water, with cover types favourable for thermoregulation, and characterised by fine substrates.

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 score0.705
Threshold uncertainty score0.843

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 head0.177
Teacher spread0.170 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueThe Atrium (University of Guelph)Same topicTurtle Biology and ConservationFrench-language works237,207