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Record W11063360 · doi:10.7202/032640ar

Soil Development as a Function of Time in the Rouge River Basin, South-Central Ontario

2007· article· en· W11063360 on OpenAlexafffundvenueabout
William C. Mahaney, K. Sanmugadas

Bibliographic record

VenueGéographie physique et Quaternaire · 2007
Typearticle
Languageen
FieldMaterials Science
TopicClay minerals and soil interactions
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of CanadaYork UniversityOregon State University
KeywordsIlliteHoloceneGeologyChloriteAlluviumSoil waterChronosequenceGeochemistryEntisolMollisolClay mineralsSoil scienceGeomorphologyOceanographyPaleontology

Abstract

fetched live from OpenAlex

Three soils of postglacial age, representing a chronosequence in the Rouge River Basin of south-central Ontario, were studied to determine variations in morphological, physical, chemical, and mineralogical properties. These soils, forming in alluvium of mixed mineralogy represent the Late HoIocene (Entisol), Middle Holocene (lnceptisol),and Early Holocene (lnceptisol) surfaces. Horizon differentiation and soil thickness increase with greater age, while pH drops slightly in the sola of the older profiles. Cation exchange capacity (CEC) and organic matter in the surface horizons increases slightly with age, while, for the most part, CaCO 3 and Ca/ Mg ratio decrease. Significant changes occur over time, especially with an increase of dithionite-extractable iron with age (from ~ 0.20 in the Late Holocene soil to ~ 0.70 in the Middle to Early Holocene profiles). Illite and illite-smectite tend to decrease with age, being replaced by small amounts of chlorite and vermiculite. In spite of some variability in parent materials due to stratification and preweathering, and minor changes in species composition, the changes in soil properties are attributed to processes of soil formation acting over time.

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)0.001
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 score0.781
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.246
Teacher spread0.233 · 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

Citations9
Published2007
Admission routes4
Has abstractyes

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