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Record W2176742760 · doi:10.1139/l11-129

The hydrological characteristics of a stream within an integrated framework of lake–stream connectivity in the Lac de Gras Watershed, Northwest Territories, Canada

2012· article· en· W2176742760 on OpenAlexaffvenueabout
Abul B. M. Baki, David Z. Zhu, Mark F. Hulsman, Brianne D. Lunn, William M. Tonn

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHydrology (agriculture)HydrographWatershedEnvironmental scienceSTREAMSSurface runoffBaseflowArcticStreamflowWater balanceWater qualityStream flowDrainage basinOutflowGeologyGeographyOceanographyEcology

Abstract

fetched live from OpenAlex

Lake–stream networks dominate much of northern Canada. This study explores the hydrological characteristics of an outlet stream from a headwater lake in the Northwest Territories of Canada. Flow hydrographs indicated that stream flow was maximal in most of the cross sections during the first week of July, and subsequently declined to zero by the first week of August 2009 and last week of August 2010. Water balance analysis indicated that the lake can be recharged by runoff from the catchment, but summer evaporation, combined with groundwater loss, caused draw down of lake level below the outflow threshold. Summer rainfall in this semi-arid environment was insufficient to overcome storage deficits to re-establish flow connectivity between lakes. The suitability of the stream sections were assessed for small and large young-of-the-year Arctic grayling based on stream geometry, stream flow characteristics, stream water temperature, and stream water quality.

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 score0.022
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.182
Teacher spread0.175 · 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

Citations18
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicHydrology and Watershed Management StudiesFrench-language works237,207