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Record W6959585713 · doi:10.1139/cjss2010-042

The impact of erosion on the classification of Mollisols in Iowa

2012· article· en· W6959585713 on OpenAlexaboutno aff

Bibliographic record

VenueBioOne Complete (BioOne) · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogens and Resistance
Canadian institutionsnot available
Fundersnot available
KeywordsMollisolUSDA soil taxonomySoil seriesSoil waterErosionSoil surveySoil classificationHydrology (agriculture)

Abstract

fetched live from OpenAlex

Fenton, T. E. 2012. The impact of erosion on the classification of Mollisols in Iowa. Can. J. Soil Sci. 92: 413-418. The fertile black soils in the Great Plains and Western States of the United States are dark brown Chernozems in the Canadian system of soil taxonomy and Mollisols, when a mollic epipedon is present, according to the United States soil taxonomy. Other primary criteria are organic carbon content, color, structure, and thickness of the mollic epipedon. Accelerated erosion can affect all of these properties and is especially critical for soils that have slope gradients of more than 2%. Accelerated erosion and erosion phases are recognized in field mapping based on the amount of A horizon remaining but criteria provided in the Soil Taxonomy guidelines conflict with procedures outlined in the Soil Survey Field Manual and result in a dichotomy between the classification system and field mapping practices. Soil map unit data for the five most extensive Mollisol soil series in Iowa that have multiple phases of slope and erosion were summarized and variations between the taxonomic and survey principles were identified. Eroded units comprise 26 to 77% of the total mapped area of the series studied and do not qualify as Mollisols under the taxonomic system. However, under the principle of following the genetic thread to classify soils, the taxonomic system should be modified to accommodate the eroded units that have the same genetic pathway as their uneroded counterparts. This could be accomplished by placing primary emphasis on the organic carbon content and waiving the color requirement for eroded soil map units.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.970
Threshold uncertainty score0.125

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)0.0000.000

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 head0.374
GPT teacher head0.260
Teacher spread0.114 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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