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Record W2771222491 · doi:10.14288/1.0347238

Ecological integrity in Stanley Park : future monitoring practices to assess long term ecological integrity

2017· article· en· W2771222491 on OpenAlexaboutno aff
Andrea McDonald, Maureen Nadeau, Karmina Cordero

Bibliographic record

VenuecIRcle (University of British Columbia) · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsEcologyEnvironmental resource managementGeographyTerm (time)Environmental scienceBiology

Abstract

fetched live from OpenAlex

In December 2006, a major windstorm event hit Stanley Park, causing significant damage to the ecology of the park. In an effort to restore the ecological integrity of the park, the Vancouver Park Board sought advice from the Stanley Park Ecology Society (SPES), only to find that no data had previously been collected regarding the park's ecology. This realization prompted SPES to formulate a long-term monitoring program that would be used to create a regularly updated State of the Park Report for the Ecological Integrity of Stanley Park (SOPEI). Long-term monitoring was conducted in both 2007 and 2009 at six sites throughout the park. These six sites consisted of three sites that had been affected by the windstorm and three sites that had not, in order to assess the differences in the sites and to determine how to effectively restore the park to its original state. In 2010, SOPEI was written, giving Stanley Park board members a thorough understanding of the current ecological state of the park. However, due to a lack of resources no further long-term monitoring was conducted, leaving no available data to create a new SOPEI report. This project focuses on creating a long-term monitoring plan that is simple and easy to use, while still maintaining the scientific integrity that is necessary to assess the ecological health of the park. The long-term monitoring plan includes a sampling database as well as a survey manual that explains how to properly sample and where the sites are located. This plan will be used for years to come, to ensure that thorough data is collected and analyzed consistently to allow for trends among data to be found. This data will provide SPES with information regarding sites that are at the most ecological risk and provide park board members an idea of where future developments should and shouldn’t go, based on their ecological significance to the park.

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)0.010
metaresearch head score (Gemma)0.010
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 score0.916
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0020.001
Scholarly communication0.0030.004
Open science0.0030.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.032
GPT teacher head0.240
Teacher spread0.209 · 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
Published2017
Admission routes1
Has abstractyes

Explore more

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