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Record W2993617583 · doi:10.1130/abs/2018am-315366

ALPINE HYDROGEOLOGY: THE CRITICAL ROLE OF GROUNDWATER IN SOURCING THE HEADWATERS OF THE WORLD

2018· article· en· W2993617583 on OpenAlexaff
Masaki Hayashi

Bibliographic record

VenueAbstracts with programs - Geological Society of America · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsHydrogeologyGroundwaterGeologyEnvironmental scienceWater resource managementGeotechnical engineering

Abstract

fetched live from OpenAlex

Groundwater discharge in alpine headwaters sustains baseflow in rivers originating in mountain ranges of the world, which is critically important for aquatic habitats, run-of-river hydropower generation, and downstream water supply. Groundwater storage in alpine watersheds was long considered negligible, but recent field-based studies have shown that aquifers are ubiquitous in the alpine zone with no soil and vegetation. Talus, moraine, and rock glacier aquifers are common in many alpine regions of the world, although bedrock aquifers occur in some geological settings. Alpine aquifers consisting of coarse sediments have a fast recession of discharge after the recharge season (e.g., snowmelt) or rainfall events, followed by a slow recession that sustains discharge over a long period. The two-phase recession is likely controlled by the internal structure of the aquifers. Spatial extent and distribution of individual aquifers determine the groundwater storage-discharge characteristics in first- and second-order watersheds in the alpine zone, which in turn govern baseflow characteristics in major rivers. Similar alpine landforms appear to have similar hydrogeological characteristics in many mountain ranges across the world, suggesting that a common conceptual framework can be used to understand alpine aquifers based on geological and geomorphological settings. Such a framework will be useful for parameterizing storage-discharge characteristics in large river hydrological models.

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 score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.236
Teacher spread0.217 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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