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Record W1018660601

Sub-grid runoff processes and hydrological modelling in the subarctic Canadian Shield

2001· article· en· W1018660601 on OpenAlexaboutno aff
Christopher Spence

Bibliographic record

VenueIAHS-AISH publication · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSurface runoffHydrology (agriculture)Subarctic climateStreamflowRouting (electronic design automation)Drainage basinEnvironmental scienceSTREAMSShieldGeologyWater storageGridGeomorphologyOceanographyGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

This paper discusses the application of a semi-distributed physically based hydrological model to the 16 000 km 2 Yellowknife River basin. The model was calibrated, but attempts at validation failed. Errors in the vertical water budget and river routing portions of the model were not large enough to account for the differences between observed and modelled streamflow. Field studies suggest the model structure did not adequately simulate the effect of storage capacity differences between land cover types on the sub-grid transfer of runoff to the stream. Runoff is delayed or prevented from reaching higher order streams because of seasonal changes in hillslope and headwater lake storage capacities, while the model structure implies that any excess water from the hillslope vertical water budget is immediately transferred.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.225
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

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

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 head0.020
GPT teacher head0.215
Teacher spread0.194 · 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 teacher head, 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
Published2001
Admission routes1
Has abstractyes

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