MétaCan
Menu
Back to cohort
Record W4409151541 · doi:10.1080/02508060.2025.2477432

Water reuse blueprint: from waste to resource

2025· article· en· W4409151541 on OpenAlex
Rania Bou Said, Rabi H. Mohtar, Sandra F. Yanni, Farah Kamaleddine, Lena Abou Jaoude

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWater International · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Reuse
Canadian institutionsAgriculture and Agri-Food Canada
FundersEuropean Commission
KeywordsBlueprintReuseResource (disambiguation)Environmental scienceWaste managementBusinessEnvironmental planningWater resource managementEnvironmental resource managementEngineeringComputer science

Abstract

fetched live from OpenAlex

This policy proposal addresses challenges in water reuse in Lebanon, including regulatory gaps, inadequate sampling and maintenance issues impacting water, soil and food. Solutions involve improving water quality analysis, fostering farmer collaboration and raising public awareness. Also, addressing operational challenges such as cost quantification, tradeoff analysis and assessing social and technical readiness are discussed. Finally, considerations include farmer willingness to pay and revenue projection for treated water. Implementing a remote data collection plan is proposed to enhance operational efficiency, reduce costs, ensure accuracy, enable realtime updates and strengthen trust in overseeing institutions, ultimately enhancing accessibility to water reuse solutions.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.240
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.009

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 head0.006
GPT teacher head0.218
Teacher spread0.212 · 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