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Record W3156461631 · doi:10.24908/iqurcp.9459

25. Snapping Turtle Conservation in Ontario

2018· article· en· W3156461631 on OpenAlexvenueaboutno aff
Rachel Wilson, P Iglesias Samuel, Molly J. Teather, Leslie Usher, Jake Windsor

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsTurtle (robot)Threatened speciesEndangered speciesHabitatCritically endangeredFisheryHabitat destructionGeographyCritical habitatNear-threatened speciesEcologyBiology

Abstract

fetched live from OpenAlex

Populations of snapping turtles are declining in Ontario. These reptiles play essential roles in wetland habitats through removal of dead animals and weeds, and their eggs provide food sources for mammals and birds. Despite being listed as a species of special concern under Ontario’s Endangered Species Act, hunting of snapping turtles is permitted in some regions of Ontario. Snapping turtles are further threatened by pollution, road mortality, and habitat loss. The developmental process of this species also acts as an obstacle to their recovery, as sexual maturity is not reached until the age of 16-19 and only 7 out of 10,000 eggs is expected to survive to adulthood. With the assistance of contacts at the Suzuki Foundation, Guelph University, and other institutions, we intend to develop a conservation strategy for snapping turtles that consists of four components. First, we recommend a government-mandated, province-wide survey of snapping turtle statistics to determine turtle populations and threats. Then we will address whether sustainable hunting is possible. The current catch allowance of two turtles per person daily, as deemed sustainable by the MNR, should be suspended until further review. Next, barriers to recovery will be addressed. Prevention of threats could be achieved through conservation area designations, signs indicating turtle presence, information on how to avoid causing turtle injury and distribution of information to persons whose property contains snapping turtle habitat. Finally, increasing public awareness of snapping turtle demographics is crucial to our strategy. Education through multiple channels will generate public interest and funding.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.109
GPT teacher head0.339
Teacher spread0.229 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2018
Admission routes2
Has abstractyes

Explore more

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