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Record W89262590 · doi:10.1007/1-4020-4738-x_10

Ground-surface water interactions and the role of the hyporheic zone

2006· book-chapter· en· W89262590 on OpenAlexafffundabout
Ken W. F. Howard, H. Maier, S. L. Mattson

Bibliographic record

VenueKluwer Academic Publishers eBooks · 2006
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersTrent University
KeywordsHyporheic zoneGroundwaterMODFLOWAquiferHydrology (agriculture)Groundwater flowGeologyRiffleHydrogeologySTREAMSSurface waterEnvironmental scienceSubsurface flowGeotechnical engineeringEnvironmental engineering

Abstract

fetched live from OpenAlex

The hyporheic zone describes a region beneath and lateral to the bed of a stream where groundwater and surface water interact. Although the existence of this zone is well recognised, the flow dynamics and mixing processes within the zone are not well understood. To investigate hyporheic zone behavior, numerical groundwater flow models were developed with MODFLOW and calibrated using data collected at a study site on the Magpie River, near Wawa, Ontario, Canada. These models were used to examine the uncertainties of hyporheic zone behaviour at pool-riffle sequences and the response of the hyporheic zone to stream flow regulation. The hyporheic zone was found to be complex and temporally sensitive to stream stage and to groundwater fluxes as determined by streambed permeability and the hydrogeological characteristics of adjacent aquifers. The size of the hyporheic zone was found to be inversely proportional to the flux of groundwater moving towards the stream, and rapid changes in river stage were determined to cause short-term reversals of flow within the hyporheic zone which have important implications on hyporheic zone organisms and their need to adapt to changing environmental conditions.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

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 communication0.0010.001
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 head0.006
GPT teacher head0.182
Teacher spread0.175 · 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 designNot applicable
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

Citations7
Published2006
Admission routes3
Has abstractyes

Explore more

Same venueKluwer Academic Publishers eBooksSame topicSoil and Water Nutrient DynamicsFrench-language works237,207