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Record W2893485273 · doi:10.3390/d10040104

Seasonal Use of Railways by Wildlife

2018· article· en· W2893485273 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueDiversity · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsLaurentian UniversityMount Allison University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWildlifeEcologyBaseline (sea)Wildlife conservationGeographyWildlife managementFaunaNocturnalDiel vertical migrationWildlife corridorEnvironmental resource managementFisheryBiologyEnvironmental science

Abstract

fetched live from OpenAlex

Despite the rapid advancements in the field of road ecology, very little research has been done in railway ecology. Basic research, such as railway use by wildlife, is relatively undocumented, albeit very important in understanding the potential negative and positive effects of railways on wildlife and ecosystems. We provide one of the first studies documenting wildlife railway use using motion-triggered cameras along a 20 km stretch of railway in Ontario. Our objectives were to develop a much-needed baseline understanding of railway use by endemic wildlife species, investigate differences in frequency of use among species, compare diurnal versus nocturnal use, and determine if railway use by wildlife was uniform or spatially varied. We found a significant proportion of medium-to-large resident mammalian fauna and several avian species non-uniformly using the studied railway. Some species used the railway as a travel corridor, while others appeared to use it incidentally. Diel and seasonal patterns of use were apparent for many species. Our findings emphasize the importance of species-specific investigations of railway ecology. The collection of baseline information on railway use by wildlife is critical in view of the dearth of available data, and we highly encourage further research in all aspects of wildlife–railway ecology.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.997

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)0.0040.001

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 head0.025
GPT teacher head0.213
Teacher spread0.189 · 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