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Record W2896141521 · doi:10.1016/j.dib.2018.10.048

Road mortality locations of small and medium-sized mammals along a partly-fenced highway in Quebec, Canada, 2012–2015

2018· article· en· W2896141521 on OpenAlexaffabout
Judith Plante, Katrina Bélanger‐Smith, Ariel G. Spanowicz, Anthony P. Clevenger, Jochen A.G. Jaeger

Bibliographic record

VenueData in Brief · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsConcordia University
Fundersnot available
KeywordsResearch articleGeographyEcologyBiologyComputer scienceLibrary science

Abstract

fetched live from OpenAlex

The data presented here consist of the locations of 839 roadkill points from four years (2012-2015) of roadkill surveys for small and medium-sized mammals (under 30 kg) from a four-lane highway in Quebec (Highway 175) during the months of May to October. Seventeen species or species groups were identified, all local to the area, and none of which were identified as species at risk, threatened, or endangered. The GPS coordinates of each roadkill event are given, along with the date, time of day (morning or evening), location (northbound or southbound lanes) and species (where possible). Within the surveyed road, 18 wildlife passages with 100 m fencing on each side of the passage entrances were built for small and medium-sized mammals. The GPS coordinates of the 18 passages and the end of each corresponding fence are also provided.

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 score0.050
Threshold uncertainty score0.801

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 communication0.0000.001
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 head0.031
GPT teacher head0.274
Teacher spread0.243 · 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

Citations4
Published2018
Admission routes2
Has abstractyes

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