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Record W2562148066 · doi:10.1111/wej.12228

Carbon curves for the assessment of embodied carbon in the wastewater industry

2016· article· en· W2562148066 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWater and Environment Journal · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Reuse
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsGreenhouse gasWastewaterEnvironmental scienceCarbon fibersSewage treatmentEnvironmental engineeringPipeline transportWaste managementElectricityEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract The water and wastewater industry has been tasked with reducing its greenhouse gas (or carbon) emissions. A key component of any emissions reduction strategy is emissions measurement. While operational emissions are reported by the sector on an annual basis, there is a lack of robust data on embodied carbon. The aim of this paper was to develop a practical solution for assessing the embodied carbon in wastewater assets. The analysis revealed a linear relationship between carbon emissions and capital investment in the construction of wastewater treatment works (1.3 tCO 2 /£1000) and wastewater pumping stations (0.3 tCO 2 /£1000). Carbon emissions from sewer construction were found to increase linearly with increasing pipe diameter, with ductile iron pipelines responsible for higher emissions than polyethylene. Operational carbon is the major component in the whole life carbon of wastewater treatment works, but future decarbonisation of the electricity grid may increase the relative importance of embodied carbon.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.127
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.231
Teacher spread0.216 · 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