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Record W2745823805 · doi:10.4236/as.2017.88062

Analysis of Impervious Surface Area, and the Impacts on Soil-Based Agriculture and the Hydrologic Cycle: A Case Study in the Agricultural Land Reserve in Metro Vancouver, British Columbia, Canada

2017· article· en· W2745823805 on OpenAlex
Ashley Rose, Julie E. Wilson, L. M. Lavkulich

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAgricultural Sciences · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsImpervious surfaceEnvironmental scienceAgricultureArable landUrbanizationLand useAgricultural landHydrology (agriculture)GeographyPopulationEcology

Abstract

fetched live from OpenAlex

The province of British Columbia, Canada, has established an Agricultural Land Reserve (ALR) to protect the most suitable soil landscapes for agriculture. Increases in population and urbanization have resulted in development challenges on ALR lands. The Metro Vancouver area is the most productive agricultural area in British Columbia as well as the most rapidly growing urban region. The increase in impervious areas has decreased the amount of arable land for soil-based agriculture and altered the hydrological cycle. Analysis using a combination of aerial imagery and GIS found that impervious areas comprise about 10 percent of the ALR within Metro Vancouver. Farm residences and greenhouses have the largest effect on reducing the soil surface for water infiltration. This decrease in area has negatively influenced the ecosystem heath of the region, as well as, decreasing the amount of agricultural land for soil based agriculture and both surface and groundwater dynamics.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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