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Record W7127193685 · doi:10.18357/wg22201644

Simulating Land Use Change in a Southern Interior Watershed in British Columbia

2016· article· W7127193685 on OpenAlexafffundabout
Markandu Anputhas, John Janmaat, Craig Nichol, Adam Wei

Bibliographic record

VenueWestern Geography · 2016
Typearticle
Language
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsLand useWatershedLand use, land-use change and forestryClimate changeAgricultureLand developmentAgricultural landWater resources

Abstract

fetched live from OpenAlex

British Columbia is a mountainous Canadian province with a limited supply of high quality agricultural land. Climate change and ongoing development are putting significant pressures on land and water resources throughout the Okanagan Valley, in the southern interior of the province. We use the CLUE-S (Conversion of Land Use and its Effects at Small regional extent) system to forecast land use change for the Deep Creek watershed, in the northern Okanagan Valley. Understanding what factors are contributing to land use change and where that change is likely to occur can help local and regional governments to better manage these changes. The calibration process highlighted the important factors affecting land use change. Model forecasts show that there will be continuing development pressure on agricultural land, an important food sovereignty issue for a mountainous province with a small area suitable for agriculture.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.211
Teacher spread0.195 · 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 designSimulation or modeling
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 routes3
Has abstractyes

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