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Record W2021006556 · doi:10.1038/npre.2011.6697.1

A hydrometric analysis of the Moose Jaw River near Burdick (05JE006): Temporal trends and frequency analyses for mean, minimum, and maximum flows

2011· preprint· en· W2021006556 on OpenAlexaffabout
Sierra Rayne, Kaya Forest

Bibliographic record

VenueNature Precedings · 2011
Typepreprint
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsSaskatchewan Polytechnic
Fundersnot available
KeywordsEnvironmental scienceStreamflowFrequency distributionSeries (stratigraphy)Maximum flow problemFrequency analysisHydrology (agriculture)ClimatologyStatisticsMathematicsGeographyDrainage basinGeology

Abstract

fetched live from OpenAlex

Abstract A hydrometric analysis over the available historical record (1973-2010) was conducted for the Moose Jaw River station near Burdick in south-central Saskatchewan, Canada. Frequency analyses on mean monthly, average annual, monthly minimum/maximum, and annual minimum flows generally yielded poor fits, and problems with negative flow predictions for mid- to long-term return periods regardless of distribution type. The annual maximum streamflow time series is reasonably well-described by linear and log Pearson Type III distributions, although both distribution types underestimate extreme maximum flows. Mann-Kendall linear time series analysis on mean monthly and annual streamflows reveals no trend in annual water yields, nor in mean monthly flows between March and October. There is ambiguity as to whether statistically significant negative time trends in overwinter period mean monthly flows and monthly minimum/maximum flows for the hydrometric station are real or whether they represent a change in measurement technique/calibration during the mid-/late-1980s.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.001
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 head0.022
GPT teacher head0.279
Teacher spread0.257 · 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.

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
Published2011
Admission routes2
Has abstractyes

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