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Record W4251243605 · doi:10.24908/iqurcp.9420

13. Mitigating Avian and Bat Mortality at Wolfe Island’s Wind Facility

2018· article· en· W4251243605 on OpenAlexvenueaboutno aff
Tearney McDermott, Victoria Ehmann, Chelsey McCord, Garrett Morandi

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsCorporationNocturnalGeographyScheduleWind powerFisheryEcologyBusinessBiologyFinanceManagement

Abstract

fetched live from OpenAlex

This research focuses on exploring existing mitigation and modification options in order to develop appropriate recommendations to aid TransAlta Corporation in curbing bird and bat mortalities on Wolfe Island. Since the construction and operation of the Wolfe Island wind facility in Frontenac County, Ontario began in 2008, it has contributed to the deaths of many local and migratory birds and bats. While official tallies of avian and bat mortalities to date vary across reports, environmentalist groups and residents alike have expressed concerns for the safety of these species citing the facility’s position on a migratory route along the eastern end of Lake Ontario as a key point of contention (Bazillauskas, A. & Yatchew, A., 2011; Blackwell, R., 2012; Dierschke, J et al., 2006). In response, the power company behind the project, TransAlta Corporation, has begun conducting its own investigation into the issue and producing bi-annual monitoring reports of mortalities but has made no significant alterations to their turbines (TransAlta Corporation, 2012). As part of an effort to reduce the direct and indirect effects of the Wolfe Island wind facility on migrating bird and bat species, this report aims to assess the suitability for TransAlta corporation of certain mitigation options such as running turbines on a rotating schedule to account for the high traffic periods throughout the year when species are likely to be most at risk and avoiding the continuous lighting which attracts nocturnal species to the towers.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.067
GPT teacher head0.336
Teacher spread0.269 · 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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