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Record W1565107572 · doi:10.1002/047147844x.aw1506

Water Logging: Topographic and Agricultural Impacts

2004· other· en· W1565107572 on OpenAlexaff
Chandra A. Madramootoo

Bibliographic record

VenueWater Encyclopedia · 2004
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsSoil waterPondingWater tableHydrology (agriculture)Environmental scienceSoil scienceSnowmeltSurface runoffGeologyLoggingSurface waterGroundwaterSnowGeotechnical engineeringGeomorphologyDrainageEnvironmental engineeringForestry

Abstract

fetched live from OpenAlex

Abstract Water logging occurs on poorly drained soils. Under periods of heavy precipitation or snowmelt, water percolates very slowly, and soils become wet in short periods of time. Some soils have inherently low ability to infiltrate and hydraulic conductivity, especially heavier clay soils. Soil compaction because of heavy farm equipment further reduces bulk density, which in turn reduces the ability to infiltrate soil. The result is that the water table accretes and may eventually rise to the land surface. High‐intensity rainfalls also lead to ponding of water on the soil surface. These conditions of surface ponding, a saturated soil profile, and gradual rise of the water table to the soil surface all lead to water logging.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.119
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)0.0050.001

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 head0.009
GPT teacher head0.199
Teacher spread0.190 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2004
Admission routes1
Has abstractyes

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