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Experimental Determination of Energy Content of Unknown Organics in Municipal Wastewater Streams

2004· article· en· W2085597890 on OpenAlexaff
Ioannis Shizas, David M. Bagley

Bibliographic record

VenueJournal of Energy Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWastewaterRaw materialWaste managementEnvironmental scienceHeat of combustionMunicipal solid wasteBenzoic acidYield (engineering)CombustionChemistryPulp and paper industryEnvironmental engineeringMaterials scienceOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

A bomb calorimetry method has been used for the first time to measure the energy content of raw municipal wastewater. The method was first validated using standard compounds (arginine, glucose, and propionic acid) and then tested with municipal sludge samples, with the results compared to previously published values. By drying a large enough sample to yield approximately 0.5 g of solid residue and using benzoic acid in a 1:1 ratio as a combustion aid, an accurate and precise measurement of the energy content of raw municipal wastewater can be made. The energy content measurements indicate that for the full-scale treatment facility examined, the potential energy available in the raw waste-water exceeds the electricity requirements of the treatment process by a factor of 9.3.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.204
Teacher spread0.193 · 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 designBench or experimental
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

Citations307
Published2004
Admission routes1
Has abstractyes

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