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Record W2558263250 · doi:10.1080/00986445.2016.1262359

A Review of Challenges and Recent Progress in Supercritical Water Oxidation of Wastewater

2016· review· en· W2558263250 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.

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

Bibliographic record

VenueChemical Engineering Communications · 2016
Typereview
Languageen
FieldEngineering
TopicSubcritical and Supercritical Water Processes
Canadian institutionsCarleton University
Fundersnot available
KeywordsSupercritical water oxidationWaste managementSupercritical fluidEnvironmental scienceCommercializationWastewaterProcess engineeringEnvironmental engineeringEngineeringChemistryBusiness

Abstract

fetched live from OpenAlex

Supercritical water oxidation (SCWO) is a promising wastewater treatment technology. It has high destruction efficiency for a broad range of organic wastes and only produces harmless end products. However, corrosion, salt deposition and plugging, and high energy consumption and operating costs have, to a great extent, restricted the successful commercialization of SCWO process. This paper first reviews the main challenges in SCWO technology, along with their comprehensive solutions. Then, the recent research progress and applications of the most common and effective methods for solving SCWO problems are examined, with the focus put on reactor material modification, advanced reactor design, energy/product recovery, and catalysis.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.678
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.052
GPT teacher head0.301
Teacher spread0.249 · 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