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Record W7132894431

Impact of Biochar on the Hydrological Performance of Extensive Green Roofs in Southern Ontario

2022· dissertation· W7132894431 on OpenAlexaffabout
Jad Saade

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldEnvironmental Science
TopicUrban Heat Island Mitigation
Canadian institutionsHudbay Minerals (Canada)
Fundersnot available
KeywordsGreen roofEvapotranspirationStormwaterWater balanceRoofHydrology (agriculture)Current (fluid)Vegetation (pathology)Biochar
DOInot available

Abstract

fetched live from OpenAlex

Green roofs are a form of green infrastructure used in urban areas to help the postdevelopment water balance mimic the pre-development balance by retaining stormwater during the wet period and restoring it as evapotranspiration (ET) during the dry period. The overall objective of the current research is threefold: (1) assessing the discharge performance (retentionand detention) over 115 rain events and vegetation growth of four configurations of extensive green roof testbeds for two variables (a) green roof plant communities, and (b) substrate amendment using biochar; (2) assessing the effect of biochar amendment on the water balance, including dew, of a green roof module planted with sedum, using a smart field lysimeter; finally (3) assessing the effect of scale on a green roof by comparing the hydrological performance of a small green roof module with that of a larger green roof testbed. Overall, the green roofs showed good hydrological performance.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.451

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.019
GPT teacher head0.277
Teacher spread0.258 · 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
Published2022
Admission routes2
Has abstractyes

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