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Record W7014613866

Potential for using paper mill fly-ash as an alternate liming material
\nand mobility and leachability of heavy metals in fly-ash and biochar
\namended agricultural soil in Western Newfoundland

2019· dissertation· en· W7014613866 on OpenAlexafffundabout

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2019
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicCoal and Its By-products
Canadian institutionsMemorial University of Newfoundland
FundersDepartment of Fisheries and Land ResourcesMemorial University of Newfoundland
KeywordsNucleofectionLiquationFusible alloyTSG101DiafiltrationProteogenomics
DOInot available

Abstract

fetched live from OpenAlex

Most agricultural soils in Western Newfoundland are acidic and need lime to raise the soil pH to
\nbe productive. Corner Brook Pulp and Paper Ltd produces a substantial amount of fly-ash which
\nis being disposed at a local landfill. This study was conducted to assess the potential for using fly-ash as a liming material for an agricultural soil (pH:5.5) in Western Newfoundland with the
\naddition of biochar for heavy metal stabilization. Heavy metal concentration in the soil and fly-ash were analysed and compared with soil and compost guidelines. Lab scale leaching and pot
\nexperiments were conducted to assess the leaching and bioavailability of heavy metals in fly-ash
\namended soil with different biochar rates. As per quality guidelines, only part of the lime
\nrequirement can be substituted by fly-ash. Biochar increased the soil pH and biomass production.
\nTotal heavy metal leached from biochar treated soils were low and unlikely to cause groundwater
\ncontamination. In general biochar reduces the leachability and the bio availability of heavy metals.
\nApplication of biochar could provide a sustainable solution for the heavy metal stabilization of
\nfly-ash treated 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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0010.001
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 head0.023
GPT teacher head0.249
Teacher spread0.225 · 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.

Study designObservational
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

Citations0
Published2019
Admission routes3
Has abstractyes

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