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Record W4417073022 · doi:10.1016/j.dibe.2025.100821

Synergistic application of modified zeolite and biochar in improving the performance of sandy vegetation concrete

2025· article· en· W4417073022 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDevelopments in the Built Environment · 2025
Typearticle
Languageen
FieldEngineering
TopicPolymer-Based Agricultural Enhancements
Canadian institutionsWSP (Canada)
FundersNational Key Research and Development Program of ChinaChina Three Gorges UniversityNational Natural Science Foundation of ChinaHubei Key Laboratory of Disaster Prevention and MitigationHubei Provincial Department of Education
KeywordsBiocharVegetation (pathology)ZeoliteAdsorptionSoil fertility

Abstract

fetched live from OpenAlex

The combined use of zeolite (ZL) and biochar (BC) can effectively address the problems of poor anti-erodibility and fertility retention capacity of vegetation concrete (VC) prepared from sandy soil. Natural ZL (NZL), especially clinoptilolite, has some disadvantages, such as presence of numerous impurities distributed in the pores and low surface activity, which lead to insufficient adsorption ability. To fully utilize the synergistic effect of ZL and BC, NZL was modified into physical (PZL), chemical (CZL), and composite-modified ZL (SZL). Results showed trend in the average pore size was SZL > CZL > PZL > natural ZL, and the changes in the functional groups on the surface of SZL was the most significant. Modified ZLs enhanced VC performance: PZL had the strongest effect on anti-erodibility, while SZL was most effective in improving fertility and retention. Our results provided a useful method for treating engineering defects in VC prepared using sandy soil.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.511
Threshold uncertainty score0.237

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 head0.005
GPT teacher head0.188
Teacher spread0.183 · 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