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Record W2809223560 · doi:10.1061/9780784481677.009

Spatial Resolution of Degree of Saturation Measurements in Unsaturated Transparent Soil Experiments

2018· article· en· W2809223560 on OpenAlexaff
Greg Siemens, Ryley Beddoe

Bibliographic record

VenuePanAm Unsaturated Soils 2017 · 2018
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsSaturation (graph theory)Image resolutionVadose zoneDegree of saturationRemote sensingEnvironmental scienceSoil scienceWater contentMoistureSpatial variabilitySoil waterComputer scienceGeologyMeteorologyGeotechnical engineeringMathematicsComputer visionGeographyStatistics

Abstract

fetched live from OpenAlex

Moisture is constantly migrating in the unsaturated zone in response to fluxes from weather systems above and saturated ground below. These moisture fluxes are often discrete in nature such as a wetting front descending from a surface. Laboratory studies of moisture migration are often limited in the number of measurement points due to spatial or cost limitations. Unsaturated transparent soil allows for direct observation and measurement of the degree of saturation regime for continuous and discontinuous experiments at high spatial and temporal resolution. Unsaturated transparent soil has previously displayed the potential providing essentially continuous degree of saturation measurements across laboratory flow experiments. Over 106 measurements can be made from a single digital image. There are theoretical and practical limitations on the obtainable spatial resolution of saturation measurements, which are dependent on the soil properties, digital camera capabilities, and image processing expertise. In this paper, the image processing method for unsaturated transparent soil experiments is presented and guidance in selecting a spatial resolution is provided.

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 categoriesMeta-epidemiology (narrow)
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 score0.131
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.086
GPT teacher head0.279
Teacher spread0.193 · 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 designBench or experimental
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

Citations3
Published2018
Admission routes1
Has abstractyes

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