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Record W1590775015 · doi:10.7202/032611ar

Morphology and Composition of Two Late Wisconsinan Soils Forming in Till and Lacustrine Deposits, Scarborough Bluffs Area, South-Central Ontario

2007· article· en· W1590775015 on OpenAlexfundvenueaboutno aff
William C. Mahaney

Bibliographic record

VenueGéographie physique et Quaternaire · 2007
Typearticle
Languageen
FieldMaterials Science
TopicClay minerals and soil interactions
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaYork University
KeywordsPaleosolGeologyWeatheringIllitePedogenesisGeochemistryClay mineralsVermiculiteMineralGlacial periodMineralogySoil waterGeomorphologyLoessPaleontologySoil scienceChemistry

Abstract

fetched live from OpenAlex

Halton Till and Glacial Lake Iroquois lacustrine sand and gravel deposits are the major surficial materials exposed at the surface of Scarborough Bluffs in South-Central Ontario. Luvisols formed in these deposits have different morphologies, including depth of weathering, complexity of horizonation, and strength of structural grades which result from parent material differences and pedogenesis. Particle size variations between the two paleosols result, in part, from different modes of deposition, and show that variable amounts of clay were produced pedogenically in the two systems. Clay mineral genesis, involving the transformation of illite and illitesmectite to vermiculite, appears to be restricted to the Iroquois sand paleosol, while some chloritization of illite occurs in both profiles. Changes in the primary mineral contents in the two paleosols suggest a similar magnitude of weathering in both systems. Distributions of vermiculite and dithionite-extractable Fe suggest some preweathering effects in the Halton Till paleosol. Morphological, mineralogical and some soil chemical properties are closely related to the physical attributes of the two different parent materials (till vs lacustrine sand and gravel).

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 score0.747
Threshold uncertainty score0.879

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 head0.017
GPT teacher head0.268
Teacher spread0.251 · 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

Citations3
Published2007
Admission routes3
Has abstractyes

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