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Record W1499709874 · doi:10.22230/jem.2011v12n1a69

Introduction: Central Interior Ecoregional Assessment

2011· article· en· W1499709874 on OpenAlexafffundabout
Pierre Iachetti, Sara Grace Howard

Bibliographic record

VenueJournal of Ecosystems and Management · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsNature Conservancy of Canada
FundersMinistry of EnvironmentMinistry of Forests, Lands and Natural Resource Operations
KeywordsEnvironmental resource managementEcoregionBiodiversityHabitat conservationContext (archaeology)Adaptive managementEcosystemGeographyHabitatEnvironmental planningEcologyEnvironmental science

Abstract

fetched live from OpenAlex

Ecoregional assessments provide a regional scale, biodiversity-based context for implementing conservation efforts by identifying a portfolio of sites for conservation action with a goal of protecting representative biodiversity and ecologically significant populations. The intent of these assessments is to create a shared vision for agencies and other organizations at the regional, state, and local levels to form partnerships and to ensure efficient allocation of conservation resources. The Nature Conservancy of Canada recently completed an ecoregional assessment of British Columbia’s Central Interior, the main components of which are presented as articles in this special issue of the BC Journal of Ecosystems and Management. These components include terrestrial ecosystems and animals, and freshwater ecosystems and species. The assessment also incorporates some new and innovative approaches to considering conservation priorities along with climate change, ecosystem services, and wildlife habitat modelling.The Central Interior Ecoregional Assessment provides a guide for prioritizing work on the conservation of habitats that support the extraordinary biological diversity of the ecoregion. Issues associated with land use and resource management planning are incredibly complex and this complexity is accelerating as a result of a changing climate and the cumulative effects of human impacts on species and ecosystems. The methods and results described in the following articles reflect the growing body of conservation planning experience.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.963

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0380.000

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 head0.026
GPT teacher head0.230
Teacher spread0.204 · 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.

Study designNot applicable
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
Published2011
Admission routes3
Has abstractyes

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