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Record W4246574595 · doi:10.32920/ryerson.14664879.v1

Performance Evaluation of Soil Cell

2021· preprint· en· W4246574595 on OpenAlexaff
Lianghao Chen

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEnvironmental scienceLeaching (pedology)NitrateEnvironmental engineeringEnvironmental chemistrySoil scienceSoil waterChemistry

Abstract

fetched live from OpenAlex

Soil Cell is a novel Low-Impact Development practice that is suitable for densely developed urban environment. This thesis seeks to gain further understanding of soil cell’s performance in terms of water quality and quality control; and to assess the exfiltration performance of perforated pipe in soil cells by monitoring an active cell. The monitoring result showed that the cell was very effective in treating particulate (90% concentration reduction), metal (91% lead concentration reduction to 53% copper concentration reduction) and phosphorus (74% concentration reduction). The cell was ineffective in treating chloride (1% concentration increase, no statistical significance) and even caused nitrate leaching (65% concentration increase). Field performance of the soil cell indicated that the inflow perforated backed up frequently, restricting the flow into the cell but laboratory testing of the perforated pipes’ hydraulic performance confirms that the pipe has a sufficient capacity to convey the flows of up to 10 L/s.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.029
GPT teacher head0.256
Teacher spread0.227 · 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 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
Published2021
Admission routes1
Has abstractyes

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