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Record W2023009451 · doi:10.1139/x03-076

Paper birch and lodgepole pine root reinforcement in coarse-, medium-, and fine-textured soils

2003· article· en· W2023009451 on OpenAlexvenueno aff
Kirstin Anne Campbell, Christopher Hawkins

Bibliographic record

VenueCanadian Journal of Forest Research · 2003
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPinus contortaSiltSoil waterEnvironmental scienceSoil textureSoil typeAgronomyBotanySoil scienceBiology

Abstract

fetched live from OpenAlex

The increased soil cohesion or reinforcement provided by roots varies among plant species and soil types. This study compared the contribution of paper birch (Betula papyrifera Marsh.) and lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) roots to soil shear resistance in two controlled environment experiments. Roots of paper birch and lodgepole pine trees contributed to a significant increase in soil shear resistance, regardless of soil type. At a shear depth of 0.20 to 0.44 m, paper birch contributed greater reinforcement than lodgepole pine. Both birch and pine provided the most root reinforcement in coarse-textured soil and the least reinforcement in medium-textured silt soil. Soil texture, porosity, and shear strength may have affected root branching of the two species, which in turn may have affected root reinforcement. At less than 1 year of age, paper birch trees planted as plugs can substantially increase soil shear strength compared with lodgepole pine in all soil types.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.030
GPT teacher head0.274
Teacher spread0.244 · 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 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

Citations15
Published2003
Admission routes1
Has abstractyes

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