MétaCan
Menu
← Back to cohort
Record W4385467230 · doi:10.4095/332017

Permafrost-related landforms and geotechnical data compilation, Yellowknife to Grays Bay corridor region, Slave Geological Province

2023· report· en· W4385467230 on OpenAlexaffabout
Peter Morse, R J H Parker, Sharon L. Smith, W E Sladen

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsPermafrostLandformGeologyDigital elevation modelTerrainGeodetic datumBaySatellite imageryPhysical geographyGeologic mapGeomorphologyRemote sensingCartographyGeographyOceanographyGeodesy

Abstract

fetched live from OpenAlex

Permafrost conditions in the Slave Geological province are not well understood. Thaw of permafrost and associated ground ice can reduce ground stability, which modifies terrain and drainage patterns and affects terrestrial and aquatic ecosystems. This presents critical challenges to northern resource development and societies where thaw of ice-rich permafrost negatively affects the integrity of ground-based infrastructure. In an effort to address this knowledge gap, this report presents a digital georeferenced database of landforms identified in permafrost terrain using high-resolution satellite imagery and provides information on geomorphic indicators of ground ice presence and thaw susceptibility. Digital georeferenced databases compiled from sedimentological and cryostratigraphic records are also provided. The landform database is focused on mapping within a 10 km-wide swath of land (8576 km2 area of interest) centred on the proposed corridors for the 773 km-long Slave Geological Province Corridor Project, NT, and the Grays Bay Road and Port Project, NU. The geomorphic features were classified and digitized using high-resolution (0.5 m) satellite imagery following an existing protocol, which was modified by using a very high-resolution (2 m) digital elevation model (DEM), and by including mapping criteria for additional features. A total of 1393 geomorphic features were mapped comprising 10 different types, which were categorized into 3 classes that include periglacial (1291), hydrological (88), and mass movement (14) features. Data from 254 geotechnical boreholes and 2243 granular deposits were compiled. Information from the compiled databases was analyzed with surficial geology information. Results indicate that the distributions and densities of mapped landforms varied substantially according to surficial geology. High ground ice contents may be quite common in glaciofluvial deposits where creep of frozen ground affects about 30% of eskers. And ground ice may be more extensive overall than the available geotechnical data indicate. Borehole and granular deposit data suggest that overburden thickness above bedrock was up to 25.5 m, and visible ground ice contents were generally between 10% and 30%, but were up to 60% in glacial blanket and glaciofluvial sediments.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.793
Threshold uncertainty score0.412

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.214
GPT teacher head0.327
Teacher spread0.114 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

Explore more

Same topicClimate change and permafrost→French-language works237,207→