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Record W7070599951

Reconnecting rattlers: Identifying potential connectivity for an urban population of Eastern Massasauga Rattlesnakes

2011· dissertation· en· W7070599951 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2011
Typedissertation
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsHabitatBiological dispersalPopulationLandscape connectivityExtinction (optical mineralogy)Wildlife corridor
DOInot available

Abstract

fetched live from OpenAlex

In an urbanizing region of Southwestern Ontario, a declining population of Eastern Massasauga Rattlesnakes ('Sistrurus catenatus catenatus') persists in taligrass prairie remnants. Maintaining an adequate level of landscape connectivity is a recommended strategy to encourage dispersal between habitat patches and to reduce the extinction risk of this genetically and ecologically distinct population. The goal of this study was to identify potential connectivity pathways between habitat patches for this species by using a GIS least-cost model and to evaluate the outputs with road mortality data. Results identified seven pathways between five core habitat patches which were validated with aerial imagery and mortality data. A subset of pathways requires further study. This research will guide the location of interventions aimed at increasing connectivity for this species, provide a basis for connectivity design for other species within the study landscape, and inform the use of a modelling approach to connectivity analysis in urban landscapes.

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)0.001
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 score0.104
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.034
GPT teacher head0.246
Teacher spread0.212 · 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
Published2011
Admission routes1
Has abstractyes

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