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Record W2105600623 · doi:10.1038/npre.2012.6785.1

Hydrologic and climate trends for the Coldwater River watershed in south-central British Columbia, Canada

2012· preprint· en· W2105600623 on OpenAlexaffabout
Sierra Rayne, Kaya Forest

Bibliographic record

VenueNature Precedings · 2012
Typepreprint
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsSaskatchewan Polytechnic
Fundersnot available
KeywordsWatershedPrecipitationEnvironmental scienceStreamflowHydrology (agriculture)Dominance (genetics)Spring (device)Climate changeWater balanceClimatologyPhysical geographyDrainage basinGeographyEcologyGeologyMeteorology

Abstract

fetched live from OpenAlex

Abstract Historical trends in streamflow and climate were investigated for the Coldwater River watershed in south-central British Columbia, Canada. Temporal increases in rainfall and total precipitation during the spring, summer, and autumn periods, as well as on an annual basis, at the city of Merritt near the mouth of the watershed, and year-round temperature increases at this site, compare with declining summertime and annual streamflows at the nearby Merritt hydrometric station on the Coldwater River. Declining summer flows at this site could reflect the dominance of temporally increasing evaporation that is offsetting increased precipitation over the same periods of the hydrologic year. Alternatively, increased water abstractions, altered regulation regimes, and/or land use changes in the watershed may also play significant/dominant roles. The relative absence of any coherent hydrological temporal patterns at the upstream Brookmere hydrometric station on the Coldwater River suggests that the net effects of warming temperatures, increasing precipitation, and any anthropogenic drivers over the past four decades are in approximate balance.

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 score0.016
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.202
Teacher spread0.196 · 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 routes2
Has abstractyes

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