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Record W2911181994 · doi:10.4095/211926

Channel changes along the lower reaches of major Mackenzie River tributaries

2000· report· en· W2911181994 on OpenAlexaff
G R Brooks

Bibliographic record

Venuenot available
Typereport
Languageen
FieldSocial Sciences
TopicArchaeology and Natural History
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsTributaryChannel (broadcasting)Hydrology (agriculture)Environmental scienceGeologyPhysical geographyGeographyOceanographyCartographyTelecommunicationsEngineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Alluvial rivers undergo lateral channel change through progressive lateral migration at bends or through channel avulsions. The floodplains of rivers experiencing lateral channel change contain geomorphic features indicative of past migration. Based on aerial photography spanning from the late 1940s early 1950s to the 1970s 1980s, insignificant lateral channel change occurred along the lowest reaches of the Root, Willowlake, Blackwater, Great Bear, Hume, Ramparts, Hare Indian, Ontaratue, and Arctic Red rivers; all of which have a meandering or meandering-straight planform. In contrast, the lowest reaches of the North Nahanni, Dahadinni, Redstone, Keele, Mountain and Carcajou rivers have all experienced significant lateral channel change, ranging from up to 3 m/year to 11 m/year. An increase in the magnitude and frequency of extreme flows arising from climate warming may cause an overall increase in the rate of bank erosion and net widening of the channel along those river reaches presently experiencing active lateral migration.

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 score0.881
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.044
GPT teacher head0.303
Teacher spread0.260 · 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

Citations3
Published2000
Admission routes1
Has abstractyes

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