MétaCan
Menu
Back to cohort
Record W2005409878 · doi:10.1002/hyp.366

Stable isotopes in river ice: identifying primary over‐winter streamflow signals and their hydrological significance

2002· article· en· W2005409878 on OpenAlexaffabout
J. J. Gibson, Terry D. Prowse

Bibliographic record

VenueHydrological Processes · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsStreamflowTributaryGeologyStable isotope ratioPrecipitationHydrology (agriculture)Ice coreSurface waterIsotopic signatureGroundwaterδ18OGroundwater rechargeEnvironmental scienceDrainage basinClimatologyAquiferMeteorology

Abstract

fetched live from OpenAlex

Abstract The process of isotopic fractionation during freezing in the riverine environment is discussed with reference to a multi‐year isotope sampling survey conducted in the Liard–Mackenzie River Basins, northwestern Canada. Systematic isotopic patterns are evident in cores of congelation ice (black ice) obtained from rivers and from numerous tributaries that are recognized as primary streamflow signals but with isotope offsets close to the equilibrium ice–water fractionation. The results, including comparisons with the isotopic composition of fall and spring streamflow measured directly in water samples, suggest that isotopic shifts during ice‐on occur due to gradual changes in the fraction of flow derived from groundwater, surface water and precipitation sources during the fall to winter recession. Low flow isotopic signatures during ice‐on suggest a predominantly groundwater‐fed regime during late winter, whereas low flow isotopic signatures during ice‐off reflect a mixed groundwater‐, surface water‐ and precipitation‐fed regime during late fall. Copyright © 2002 John Wiley & Sons, Ltd.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0050.000

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 head0.025
GPT teacher head0.219
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.

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

Citations47
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueHydrological ProcessesSame topicArctic and Antarctic ice dynamicsFrench-language works237,207