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Record W3110844606 · doi:10.17762/de.vi.965

Restricted Effect of Two Plant Root Systems on the Crack Expansion of China Yunnan Laterite under Dry-wet Cycle

2020· article· en· W3110844606 on OpenAlexvenueno aff
Guojian Feng Weiwei Zhu

Bibliographic record

VenueDesign Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLateriteRoot systemEnvironmental scienceMaterials scienceAgronomyBiologyMetallurgy

Abstract

fetched live from OpenAlex

In order to research the restricted effect of hedera nepalensis root systems and heteropogon contortus root systems on the crack expansion of Yunnan laterite under dry-wet cycle, this paper prepares Yunnan laterite with certain moisture content, and makes the compacted samples of pure laterite and composite soil mixed with root systems by adopting hedera nepalensis root systems and heteropogon contortus root systems respectively, and then simulates the dry-wet cycle of laterite in engineering (i.e., rainfalls and evaporations), measures the crack width of samples experiencing different cycles, and makes statistical analysis on the average maximum crack width of samples in all groups by adopting the method of indoor spraying and natural drying. The result indicates that, 10% and 20% mixed hedera nepalensis root systems can exert obvious restrictions on the crack expansion of Yunnan laterite after dry-wet cycle, while 30% mixed hedera nepalensis root systems and 10% mixed heteropogon contortus root systems can also restrict the crack expansion of Yunnan laterite, but the restricted effect is weaker. As for 20% and 30% mixed heteropogon contortus root systems, composite soil samples will disintegrate after the 2nd dry-wet cycle.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.017
GPT teacher head0.200
Teacher spread0.184 · 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 designBench or experimental
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

Citations2
Published2020
Admission routes1
Has abstractyes

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