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Record W4395693878 · doi:10.52939/ijg.v20i4.3151

Multiscale Space-Time Analysis of Environmental Changes in the Oil Sands Area (Alberta, Canada)

2024· article· en· W4395693878 on OpenAlex

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Geoinformatics · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsFuture EarthUniversity of Calgary
FundersGovernment of AlbertaAlberta Environment and Parks
KeywordsOil sandsGeographyEnvironmental scienceGeologyMeteorologyCartography

Abstract

fetched live from OpenAlex

Our study encompasses the Oil Sands Area (OSA) within northern Alberta, Canada, which has experienced substantial environmental changes over the last decades, in association with natural and anthropogenic disturbances. Using composites of Landsat imagery for 5-year intervals between 2000 and 2020, we performed two parallel geospatial analyses to assess environmental changes, examining landscape metrics and spectral indices. Landscape metrics were calculated from land use/land cover maps derived from a Random Forest supervised classification. Spectral indices included Normalized Difference Vegetation Index (NDVI) and Normalised Difference Built-up Index (NDBI), among others. Both hierarchical zonal analysis of spectral indices and zonal landscape metrics were calculated based upon two different aggregations of nested drainage basin features from hydrologic unit code (HUC - Watersheds of Alberta). Spatial contiguity of changes was evaluated by hotspot analysis. HUCs determined to experience significant changes at coarse aggregation level were examined at finer level. The combination of landscape metrics and zonal analysis provided evidence of substantial, yet localized, areas of changing trends. Mixed forest experienced the most significant changes; urban/barren areas initially increased and later decreased, indicating change both in agricultural and human-made areas.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.999

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)0.0020.000

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 head0.003
GPT teacher head0.190
Teacher spread0.186 · 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