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The Effects of Climatic Variability on Estimates of Recharge from Temperature Profiles

2005· article· en· W2124158659 on OpenAlex
Grant Ferguson, Allan D. Woodbury

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGround Water · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of ManitobaSt. Francis Xavier University
FundersNatural Sciences and Engineering Research Council of CanadaManitoba Hydro
KeywordsGroundwater rechargeEnvironmental scienceAdvectionReliability (semiconductor)TRACERGroundwaterHydrology (agriculture)GeologyAquiferGeotechnical engineeringPower (physics)Thermodynamics

Abstract

fetched live from OpenAlex

Using heat as a tracer allows for estimation of ground water recharge rates based on subsurface temperature measurements. While possible in theory, it may be difficult in practice to discriminate the effects of climate from the effects of ground water advection. This study uses synthetic simulations to determine the influence of variability of ground surface temperature (GST) on the ability to estimate vertical specific discharge from temperature profiles. Results suggest that in cases where temperature measurements are sufficiently deep and specific discharge is sufficiently high, estimates of specific discharges will be reasonably accurate. Increasing the number of times temperatures are measured, or producing models that incorporate variations in GST, will increase the reliability of any studies using temperatures to estimate specific discharge. Furthermore, inversions of temperature measurements should be combined with other methods of estimating recharge rates to improve the reliability of recharge estimates.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.218

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)0.0000.000

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 head0.005
GPT teacher head0.205
Teacher spread0.200 · 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