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Record W2320858868 · doi:10.1061/9780784412473.024

Hydraulic and Hydrological Regime of Ice-Affected Channels at Freezeup

2012· article· en· W2320858868 on OpenAlexaff
Benoit Turcotte, Brian Morse, François Anctil

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTributaryChannel (broadcasting)Environmental scienceStage (stratigraphy)Hydrology (agriculture)DischargeWatershedPrecipitationGeologyDrainage basinMeteorologyGeographyEngineeringComputer science

Abstract

fetched live from OpenAlex

Measuring the channel discharge of an ice-affected channel is imperative for socio-economic and ecological reasons. Under open water conditions, the channel discharge can be easily obtained using a rating curve. The production of ice and the development of ice features such as a floating ice cover and anchor ice accumulations significantly affect the stage-discharge relationship. In addition, they significantly impact the actual channel discharge. While in-situ discharge measurements cannot always be performed in mid-winter and even less so during freezeup, it is nonetheless possible to evaluate the channel discharge by understanding the watershed dynamics and ice processes that take place along the channel and its tributaries. This paper reports water stage and discharge trends of the freezeup period along channels of distinct sizes and morphologies. These trends are associated with characteristic ice processes at the local and watershed scales, and are related to other parameters such as the air temperatures and precipitation. Identifying typical ice processes signatures can help engineers and hydrologists to distinguish between ice-induced water stage variations and actual discharge variations. Despite the complexity of freezeup processes taking place along cold and temperate regions channels, evaluating the discharge of any channel can be facilitated by understanding the type and timing of ice processes and by monitoring some key parameters that could complement water stage records.

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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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

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 head0.027
GPT teacher head0.214
Teacher spread0.188 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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