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Record W2266174682 · doi:10.13031/2013.7389

Incorporation and Evaluation of a River Water Quality Model to NAPRA WWW Decision Support System

2001· article· en· W2266174682 on OpenAlexaboutno aff
Kyoung Jae Lim, Bernard A. Engel, Amots Hetzroni

Bibliographic record

Venue2001 Sacramento, CA July 29-August 1,2001 · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPermeameterHydraulic conductivityField (mathematics)AnisotropySpatial variabilityMathematicsSoil scienceMineralogyGeologyHydrology (agriculture)StatisticsOpticsSoil waterGeotechnical engineering

Abstract

fetched live from OpenAlex

The spatial variability of the saturated hydraulic conductivity (Ks ) of a greenhousebanana plantation volcanic soil was investigated with three different permeameters: a) thePhilip-Dunne field permeameter, an easy to implement and low cost device; b) the Guelph fieldpermeameter; and c) the constant-head lab permeameter. Ks was measured on a 14x5 array of2.5mx5m rectangles at 15 cm depth using the above three methods. In the case of the labpermeameter a sinusoidal spatial variation of Ks was coincident with the underlying alignment ofbanana plants on the field. To discard the possibility of an artifact the original 70 point mesh wasdoubled by intercalation of a second 14x5 grid, such that the lab Ks was finally determined on a140 points 2.5x2.5 square grid. Far from diluting such anisotropy this was further strengthenafter inclusion of the new 70 points. The porosity determined on the same lab cores shows asimilar sigmoidal trend, thus pointing towards a plausible explanation for such variability. In factboth parameters follow a power-law relation of the form Ks=a*porosity^b (R=0.62) as stated byArchie's law. Although the two-field methods: Guelph and Philip-Dunne, also follow a similaralignment trend this is not so evident, suggesting that additional factors affect Ks measured inthe field. Finally geostatistical techniques are used to further investigate this spatialdependence. A log-transformation was found to be both a symmetrizing and variance stabilizingtransformation of the Ks data.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.052
GPT teacher head0.308
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

Study designSimulation or modeling
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
Published2001
Admission routes1
Has abstractyes

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