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Record W4386293643 · doi:10.24908/ohi.v1i2.16448

The Utilization of Recycled Gypsum as a Soil Amendment

2023· article· en· W4386293643 on OpenAlexaffabout
Meghan Watson, Katelyn Starr

Bibliographic record

VenueOne Health Innovation · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsQueen's University
Fundersnot available
KeywordsAmendmentGypsumEnvironmental scienceHazardous wasteWaste managementHuman healthSoil waterSalt (chemistry)Environmental protectionEnvironmental engineeringEngineeringGeologyChemistryLawEnvironmental healthSoil science

Abstract

fetched live from OpenAlex

Road salt, specifically sodium chloride (NaCl), is commonly used in Canada as a de-icer to keep roadways safe during the winter months. However, the increasing amounts used annually contaminate water systems and soils with hazardous levels of chemicals, posing a threat to humans, non-human animals, and the environment. As previous initiatives to address this issue have been expensive and difficult to implement, a One Health approach is required to minimize the impacts of road salt use. This article proposes a non-toxic solution to reduce the impacts that road salt has on all aspects of the One Health triad. This solution involves the use of recycled gypsum from clean drywall as a soil amendment to reverse road salt-induced damage to the soil. This practice would also reduce the amount of construction waste that ends up in landfills. If deemed successful, this practice could be expanded to other areas in Canada to mitigate the damage of road salts on the ecosystem.

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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.063
GPT teacher head0.322
Teacher spread0.259 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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