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Record W6959730610 · doi:10.1139/cjss2011-028

Proposed classification for human modified soils in Canada: Anthroposolic order

2012· article· en· W6959730610 on OpenAlexaboutno aff

Bibliographic record

VenueBioOne Complete (BioOne) · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Geostatistics and Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsSoil waterPedogenesisLand reclamationNatural (archaeology)Soil carbonTotal organic carbonDrainageSoil horizon

Abstract

fetched live from OpenAlex

Naeth, M. A., Archibald, H. A., Nemirsky, C. L., Leskiw, L. A., Brierley, J. A., Bock, M. D., VandenBygaart, A. J. and Chanasyk, D. S. 2012. Proposed classification for human modified soils in Canada: Anthroposolic order. Can. J. Soil Sci. 92: 7-18. With increasing anthropogenic activity, the areal extent of disturbed soils is becoming larger and disturbances more intense. Regulatory frameworks must incorporate reclamation criteria for these disturbed soils, requiring consistent descriptions and interpretations. Many human altered soils cannot be classified using the Canadian System of Soil Classification (CSSC), thus an Anthroposolic Order is proposed. Anthroposols are azonal soils, highly modified or constructed by human activity, with one or more natural horizons removed, removed and replaced, added to, or significantly modified. Defining features are severe disruption of soil forming factors and introduction of potentially new pedogenic trajectories. Disturbed layers are anthropic in origin and contain materials significantly modified physically and/or chemically by human activities. Three great groups are defined by presence of anthropogenic artefacts and organic carbon content. Six subgroups are based on a cover soil layer with higher organic carbon content than the profile below it, on depth of disturbance, on drainage characteristics and water regime at the site. Some new phases and modifiers, in addition to traditional ones used in the CSSC, are based on chemical and physical properties and origins of anthropogenic artefacts. The proposed classification has been successfully applied to reclaimed profiles and is ready for widespread field testing.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0130.013
Science and technology studies0.0050.002
Scholarly communication0.0030.001
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.341
GPT teacher head0.272
Teacher spread0.069 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2012
Admission routes1
Has abstractyes

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