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Record W1963565679 · doi:10.1139/l08-075

Stabilization of the phosphatic wastes using high calcium ash in Jordan

2008· article· en· W1963565679 on OpenAlexvenueno aff
Nafeth Abdel Rahman Abdel Hadi

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsnot available
Fundersnot available
KeywordsBottom ashCompressive strengthEnvironmental scienceMasonryWaste managementCombustionCementGeologyMineralogyFly ashPulp and paper industryMetallurgyChemistryMaterials scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

A significant amount of phosphatic waste and phosphatic overburden soils are stockpiled in the Al-Rusaifa area of Jordan. Research was completed on stabilizing this waste by mixing it with limy ash that was produced by the direct combustion of bituminous limestone. Doing so minimizes the environmental impact of the huge amount of phosphatic waste, and produces a product that can be used in various construction projects like earth works, pavement works, production of masonry blocks and curbstones. A variety of laboratory tests were completed to determine the suitability of the stabilized waste for these different uses. The S2 ash was produced by the direct combustion of bituminous limestone at 950 °C while the S3 ash was produced at 525 °C. Tests showed that the unconfined compressive strength of the parent phosphatic waste was raised from 1.5 kg/cm2 to 28.8 kg/cm2 for the S2 and to 22.4 kg/cm2 for the S3 ash treated samples. The new results were obtained despite a decrease in the maximum dry density to 1.47 g/cm3 when compared to 1.89 g/cm3 of the original untreated phosphatic waste. The soaked California bearing ratio was raised from 2.4% to 120%. The tests confirmed the suitability of the stabilized waste for a variety of construction applications.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.013
GPT teacher head0.178
Teacher spread0.165 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

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