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Record W3157549978 · doi:10.24908/iqurcp.9429

16. The Impacts of Road Salting on Wildlife in Kingston, Ontario

2018· article· en· W3157549978 on OpenAlexvenueaboutno aff
L Goddijn- Murphy, Courtney Primeau, Marissa Robinson, Natalie Rook

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsWildlifeLivelihoodWildlife conservationSaltingNatural resource economicsEnvironmental planningEnvironmental protectionEnvironmental scienceBusinessEnvironmental resource managementGeographyAgricultureEcologyEconomics

Abstract

fetched live from OpenAlex

The cold icy winter climate of Kingston is dangerous for driving commuters and can be treacherous for pedestrians. To prevent slippery conditions, roads are often salted using a basic sodium chloride mixture which has been shown in many studies to be detrimental to wildlife. Generally, policy makers and governing bodies have fought harder to ensure the safety of human lives over those of plants and animals – decisions that have caused road salting to continue for many years. We believe that the harmful impacts on the environment are numerous and should no longer be overlooked by the decision makers. In response to this problem, we are confident that there are solutions that can be implemented which can protect the livelihood of humans in the winter and reduce the negative impacts that are being forced on the environment. For example, using environmentally friendly alternatives such as sand and EcoTraction may have significant impacts on the conservation of wildlife throughout Eastern Ontario.

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 score0.024
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.075
GPT teacher head0.349
Teacher spread0.274 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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Same venueInquiry Queen s Undergraduate Research Conference ProceedingsSame topicWildlife-Road Interactions and ConservationFrench-language works237,207