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Record W4293193173 · doi:10.4095/329643

Distributions of degraded and intact lithalsas, North Slave region, Northwest Territories

2022· report· en· W4293193173 on OpenAlexaffabout
Peter Morse, A C A Rudy

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsThermokarstPermafrostPhysical geographyGeologySatellite imagerySTREAMSAerial photosSatelliteHydrology (agriculture)Open waterRemote sensingGeographyOceanographyComputer science

Abstract

fetched live from OpenAlex

The main objective of this report is to provide an inventory of current (intact or degrading) and old (completely degraded) lithalsas in a representative study area of the southern North Slave region between Behchoko and Yellowknife in the Northwest Territories. A lithalsa is an ice-rich mound of permafrost that causes the soil to settle downward and water to pond if the ice core thaws (thermokarst pond). Lithalsas, widespread in this region, are therefore very sensitive to thawing. This inventory should help to better understand current and future permafrost conditions, and is based directly on the GSC's Open File 7255, which provides an inventory of many lithalsas in the region, as well as on the GSC's Open File 8205, which provides an inventory of thermokarst pond development between 1945 and 2005 in the same study area. Using high-resolution satellite images, we completed the inventory of 475 intact lithalsas in the study area. Then, by combining our field observations of surface geomorphology of degrading lithalsas with recognizable geomorphic patterns in the same satellite imagery, we developed criteria to identify and map them and we developed an inventory of 556 completely degraded lithalsas. The inventories and databases are prepared for assessment of the relations between elevation, surface geology and distribution of lithalsas, and the trajectory of thermokarst development in the region. The inventories included with this report can be used directly in a Geographic Information System (GIS).

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)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.067
GPT teacher head0.264
Teacher spread0.197 · 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
GenreOther

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
Published2022
Admission routes2
Has abstractyes

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