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Record W2910619444 · doi:10.4095/222393

Landslide inventory of the south-central Mackenzie River valley region, Northwest Territories

2006· report· en· W2910619444 on OpenAlexaffabout
David Huntley, A Duk-Rodkin, C Sidwell

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsLandslideGeologyRiver valleyGeomorphologyArchaeologyGeographyPhysical geographyAerial photosHydrology (agriculture)Remote sensingGeotechnical engineering

Abstract

fetched live from OpenAlex

As part of the Northern Energy Development Mackenzie Valley Project, an inventory of terrain and geomorphic processes is currently being compiled for the Camsell Bend (NTS 95 J), Root River (NTS 95 K), Dahadinni River (NTS 95 N), and Wrigley (NTS 95-O) 1:250 000 NTS map sheets. The interaction between high relief, steep slopes, heavy precipitation, complex tectonic and glacial history, and the range of surficial deposits and bedrock along the Mackenzie River valley transportation corridor has resulted in a variety of landslide types. Earth materials most susceptible to failure are colluvial, glaciolacustrine, alluvial, and organic deposits containing discontinuous permafrost. Till and glaciofluvial outwash are the most stable earth materials. Channel migration has triggered numerous complex landslides along the Mackenzie River. Removal of stream-side vegetation and soil also leads to retrogressive-thaw flows and slides in ice-rich terrain.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.989

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.214
Teacher spread0.201 · 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
Published2006
Admission routes2
Has abstractyes

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