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Record W3048824984 · doi:10.4095/326821

Understanding prairie landslides: current research in the Assiniboine River valley, Manitoba-Saskatchewan (2019-2020)

2020· report· en· W3048824984 on OpenAlexaffabout
David Huntley, Peter Bobrowsky, Drew Rotheram-Clarke, Robert Cocking, J Joseph

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsLandslideCurrent (fluid)ArchaeologyGeographyGeologyHydrology (agriculture)ForestryPhysical geographyGeomorphologyGeotechnical engineeringOceanography

Abstract

fetched live from OpenAlex

The mandate of Inter-Departmental Letter of Agreement 5170 (IDLA-4755) between Natural Resources Canada (NRCan) and Transport Canada (TC) was to research and monitor landslides where vital railway infrastructure and operations, public safety, and the environment are at risk. IDLA-4755 combined research and development of landslide monitoring technologies in the Thompson River valley, British Columbia with new activities in the Assiniboine River valley along the borders of Manitoba and Saskatchewan, and other sites in Canada. This report focuses on the 2019-2020 results and interpretation of: a) monitoring with real-time kinematic global navigational satellite system (RTK-GNSS); and, b) photogrammetry using unmanned aerial vehicles (UAV) and commercially available software in the Assiniboine River valley.

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)0.001
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 score0.017
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.195
GPT teacher head0.355
Teacher spread0.160 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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