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Record W2570430231

TRA-913: BAT SPECIES AT RISK AND IMPLICATIONS TO INFRASTRUCTURE PROJECTS IN ONTARIO

2016· article· en· W2570430231 on OpenAlexaboutno aff
Melissa Straus, Nicole Kopysh, Andrew Taylor

Bibliographic record

VenueScholarship@Western (Western University) · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyEnvironmental planningBusinessEnvironmental resource managementEnvironmental science
DOInot available

Abstract

fetched live from OpenAlex

The Ontario Endangered Species Act (ESA 2007) provides protection of listed bat species and their habitat, including Eastern Small-footed Myotis (Myotis leibii), Little Brown Myotis (Myotis lucifugus), and Northern Myotis (Myotis septentrionalis); all of which have been identified as Endangered. The Tri-coloured Bat (Perimyotis subflavus) is currently under review and may be identified at risk in the near future. Bats are listed as a result of the spread of White-nose Syndrome (WNS), a fungal pathogen that has resulted in mass mortality events within hibernation sites. Through the use of two case studies we identify a number of challenges in accounting for bat species at risk during development, including identification and confirmation of natural maternity roost habitat. In our experience, woodlands have been considered general habitat regardless of confirmation of use if bat species at risk are recorded in the Project Area. This has implications for development projects that propose to remove any treed habitat, however; there are some general mitigation measures that, in most cases, can be implemented to avoid impacts. This includes timing restrictions for tree clearing, habitat restoration and compensation, and retention of suitable roost trees. Failure to consider protected habitat for Endangered bats early in the planning process could have consequences for project schedules. It is recommended that development projects proposing tree removal identify potential bat habitat features early in the planning process and engage in early and ongoing consultation with the Ministry of Natural Resources and Forestry (MNRF).

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)0.003
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 score0.045
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.075
GPT teacher head0.255
Teacher spread0.180 · 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
Published2016
Admission routes1
Has abstractyes

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