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Record W3172646742 · doi:10.5194/egusphere-egu21-9232

Delineation of soil drainage class by electromagnetically measurements of soil magnetic susceptibility

2021· article· en· W3172646742 on OpenAlex
Farzad Shirzaditabar, Richard J. Heck, Mike Catalano

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMagnetic and Electromagnetic Effects
Canadian institutionsGeneral Electric (Canada)University of Guelph
Fundersnot available
KeywordsHydric soilSoil waterSoil scienceDrainageTopsoilEnvironmental scienceMaghemiteSoil typePedogenesisSoil healthHydrology (agriculture)Soil organic matterGeologyMagnetiteGeotechnical engineering

Abstract

fetched live from OpenAlex

<p>Soil has the most important role in agriculture. For instance, it prevents run off and also through its capacity for storing water, it acts as a water reservoir and provide water resources for plant roots. Water retention characteristics, nutrient holding capacities and solute transport of soil can affect its productivity. So, the plant growth is directly associated with the type of soil drainage. The prediction of soil drainage classes is one of the major steps in developing crop modelling. Among different physical and chemical soil health indicators, soil magnetic susceptibility (MS) is a promising factor for soil surveying because it is strongly affected by soil drainage class. The extremely reducing conditions, present in hydric soils, significantly enhance dissolution of soil ferrimagnetic minerals such as magnetite and maghemite. Since the MS of soils is mainly controlled by magnetite and maghemite concentrations, therefore MS values are typically very low in hydric, i.e. poorly drained or gleyed, soils.</p><p>The common method for measuring soil MS is utilizing handheld or laboratory MS meters (e.g. Bartington MS2 sensors). Such MS meters are required soil specimen to be available to directly measure MS of that specimen. So, their application is limited to surface soils, soil exposures and sampled soils. Other types of instruments for quickly measuring soil properties are electromagnetic induction (EMI) instruments. Although the EMI instruments were primarily invented to measure electrical conductivity (EC) of the topsoil for assessment of soil salinity, they can also be utilized to measure absolute value of the volume MS of the topsoil. These volume MS values can be further processed and inverted to reveal MS variations of soil layers.</p><p>In this study, 1-D inversion of volume MS data, measured by Geonics EM38 instrument in both vertical and horizontal magnetic dipole configurations, was done to calculate MS of selected soil profiles in order to delineate soil drainage classes. Besides, laboratory measurements of volume and mass-specific MS of soil core samples, collected in the same soil profiles, were done using Bartington MS2B and MS2C sensors. Results show a strong and positive relationship between MS values measured in the laboratory and volume MS recovered from inversion technique. Furthermore, the results reveal that MS in a well drained profile is higher than that of a poorly drained profile. Since EMI measurements of soil MS are done quickly in the field, then using surface MS measurements facilitates hydric soil delineation in a faster and more precise way.</p>

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.

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 score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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