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Record W2164106898 · doi:10.4141/s01-019

Magnetic susceptibility of Gleysolic and Chernozemic soils in Saskatchewan

2002· article· en· W2164106898 on OpenAlexvenueaboutno aff
E. de Jong

Bibliographic record

VenueCanadian Journal of Soil Science · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGeomagnetism and Paleomagnetism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGleysolSoil waterSoil scienceSoil surveyChemistryEnvironmental science

Abstract

fetched live from OpenAlex

In Saskatchewan, Gleysolic and Chernozemic soils often are found close to each other in hummocky terrain. Magnetic susceptibility (χ) is known to be reduced in poorly drained soils compared to well-drained soils, and this study investigated the use of χ as an accessory criterion for identifying Gleysols. Archived soil samples from an area near Saskatoon were analyzed for χ and sand content, and where necessary for organic and inorganic C and oxalate (Feo) and dithionite (Fed) extractable iron. The lowest χ values were found in Humic Luvic Gleysols and the highest in Dark Brown Chernozems; Rego and Orthic Gleysols and Rego Humic Gleysols had χ values that overlapped those of the Dark Brown Chernozems. Within the upper 50 cm of the profile, all Gleysols except the Rego Humic Gleysol had at least one horizon with %chi; less than 150 × 10 -9 m 3 kg -1 . The χ of the A and B horizons was negatively correlated to their Feo/Fed ratios, and not correlated to their sand content. The χ of the deep tills was positively correlated to sand content, and not correlated to Feo/Fed ratio. It appears that χ may be as useful as the Feo/Fed ratio for assisting in classifying Gleysols. Key words: Magnetic susceptibility, Gleysols, Chernozems, Feo, Fed, CaCo 3

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.998

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 studies0.0000.001
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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations17
Published2002
Admission routes2
Has abstractyes

Explore more

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