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Record W6903551255 · doi:10.1139/cjss2011-014

Luvisolic soils of Canada: Genesis, distribution, and classification

2011· article· en· W6903551255 on OpenAlexaboutno aff

Bibliographic record

VenueBioOne Complete (BioOne) · 2011
Typearticle
Languageen
FieldMaterials Science
TopicClay minerals and soil interactions
Canadian institutionsnot available
Fundersnot available
KeywordsEluviumPodzolWeatheringSoil waterLessivageHorizonSoil horizon

Abstract

fetched live from OpenAlex

Lavkulich, L. M. and Arocena, J. M. 2011. Luvisols of Canada: Genesis, distribution, and classification. Can. J. Soil Sci. 91: 781-806. Luvisols link the soil continuum on the Quaternary landscapes. These soils are developed from parent materials rich in Ca and Mg in a relatively humid climate. An acidic eluvial horizon overlying a phyllosilicate-enriched illuvial Bt horizon is the common horizon sequence in Luvisolic soils. Lessivage or the translocation of clays with minimal chemical alteration is the characteristic soil-forming process and results to the diagnostic Bt horizon with well-developed, oriented clay skins or cutans. These soils commonly form intergrades with Chernozems, Podzols and Vertisols. With time, the eluvial horizons experience increased chemical weathering and further release of sequioxides to form Brunisolic and Podzolic sequences within the eluvial Ae in biseqeual soils. Lessivage significantly influences several ecosystem functions of soils. The high amounts of phyllosilicates in the Bt horizon serve as one of the most active sorption sites in soils for metals and organic materials including soil carbon. Sorption of cations takes place through cation exchange reactions and determines the availability of cations to plant roots as well as in the “colloid facilitated transport” of strongly sorbing metals and organic pollutants. Clays in Bt can be restrictive to water and air movement as well as to root growth and distribution. Agricultural and forestry practices such as tillage can compact the structure of Luvisols and may decrease soil productivity.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score0.900

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 head0.366
GPT teacher head0.254
Teacher spread0.112 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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