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Record W2610449417 · doi:10.1002/cjce.22885

Efficient treatment of actual pharmaceutical wastewater by wet oxidation process in subcritical water apparatus

2017· article· en· W2610449417 on OpenAlexvenueno aff
Umme Marium Ahmad, Yuan Pu, Wei-Kang Qi, Neil R. Foster, Jian‐Feng Chen, Dan Wang

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsWastewaterNitriteChemical oxygen demandSewage treatmentAmmoniumNitrateChemistryWastewater quality indicatorsPulp and paper industryEnvironmental scienceEnvironmental engineeringOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Abstract Pharmaceutical wastewater is a typical persistent refractory organic industrial wastewater. In this work, a simple, one‐step method for the treatment of pharmaceutical wastewater was developed using wet oxidation (WO) in a subcritical water apparatus, with detailed studies on the effects of operating parameters, including the temperature of the system, the ratio of reactants, and pH of the wastewater. Under optimized experimental conditions, efficient treatment of actual pharmaceutical wastewater was achieved, with removal of 100 % chemical oxygen demand (COD), 98 % nitrate ion, 98 % nitrite ion, and 68 % ammonium ion. Our results suggest that the WO process, using a subcritical water apparatus, is a promising method of treatment for pharmaceutical wastewater.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 studies0.0000.000
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 head0.018
GPT teacher head0.264
Teacher spread0.246 · 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

Citations12
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical Engineering→Same topicPharmaceutical and Antibiotic Environmental Impacts→French-language works237,207→