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Record W4392600844 · doi:10.1021/acs.biomac.3c01294

Benchmarking the Humidity-Dependent Mechanical Response of (Nano)fibrillated Cellulose and Dissolved Polysaccharides as Sustainable Sand Amendments

2024· article· en· W4392600844 on OpenAlexaff
M-Haidar Ali Dali, Roozbeh Abidnejad, Mohamed Hamid Salim, Mamata Bhattarai, Monireh Imani, Orlando J. Rojas, Luiz G. Greca, Blaise L. Tardy

Bibliographic record

VenueBiomacromolecules · 2024
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSoil waterCelluloseCutinNanocelluloseEnvironmental scienceChemistryChemical engineeringEnvironmental chemistryMaterials scienceSoil scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Soil quality is one of the main limiting factor in the development of the food sector in arid areas, mainly due to its poor mechanics and lack of water retention. Soil's organic carbon is nearly absent in arid soils, though it is important for water and nutrient transport, to soil mechanics, to prevent erosion, and as a long-term carbon sink. In this study, we evaluate the potential benefits that are brought to inert sand by the incorporation of a range of, mainly, cellulosic networks in their polymeric or structured (fiber) forms, analogously to those found in healthy soils. We explore the impact of a wide range of nonfood polysaccharide-based amendments, including pulp fibers, nanocellulose, cellulose derivatives, and other readily available polysaccharide structures derived from arthropods (chitosan) or fruit peels (pectin) residues. A practical methodology is presented to form sand-polymer composites, which are evaluated for their soil mechanics as a function of humidity and the dynamics of their response to water. The mechanics are correlated to the network of polymers formed within the pores of the sandy soil, as observed by electron microscopy. The response to water is correlated to both the features of the network and the individual polysaccharides' physicochemical features. We expect this work to provide a rapid and reproducible methodology to benchmark sustainable organic amendments for arid soils.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
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 head0.014
GPT teacher head0.292
Teacher spread0.278 · 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 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

Citations7
Published2024
Admission routes1
Has abstractyes

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