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Record W2128821274 · doi:10.2478/v10183-012-0013-4

Properties of selected soils from the sub−arctic region of Labrador, Canada

2012· article· en· W2128821274 on OpenAlexaboutno aff
Tony R. ‎Walker

Bibliographic record

VenuePolish Polar Research · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Geostatistics and Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsPodzolSoil waterRegosolGleysolLoamSoil scienceSoil seriesSoil morphologyTotal organic carbonSoil classificationSoil horizonHumusGeologySoil organic matterOrganic matterEnvironmental scienceEnvironmental chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract Atotal of 212 soil profiles were described and assessed for physical and chemical properties during July 2006 as part of an Ecological Land Classification study along the Churchill River in central Labrador. Two major soil types were found in the study area along the Churchill River: Podzols and Organic soils. Podzolic soils covered approximately 60% and Organic soils occurred in 24% of the study area. Approximately 15% of the study area was classified as rock and other unconsolidated material. Summary results and a sub−set of the following soil units (from 10 soil profiles) are presented here and were distin− guished according to the Canadian System of Soil Classification (CSSC) (Soil Classifica− tion Working Group 1998): Orthic Humo−Ferric Podzol, Placic Ferro−Humic Podzol, Gleyed Humo−Ferric Podzol, Sombric Humo−Ferric Podzol, Gleyed Regosol and Orthic Luvic Gleysol. The basic properties of the soil units identified above included: (i) morpho− logical descriptions of soil profiles with differentiated horizons; (ii) field−texture tests were used to determine classes and physical properties of sands, silts, loams and occurrence of mottles; and (iii) a range of soil chemical composition of different horizons ( e.g. , pH, total organic carbon [TOC] and select metal concentrations) which indicated no anthropogenic contamination above background concentrations in the area.

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)0.001
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 score0.385
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.061
GPT teacher head0.278
Teacher spread0.217 · 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

Citations13
Published2012
Admission routes1
Has abstractyes

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