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Record W3001327070 · doi:10.1080/01496395.2020.1718706

Batch adsorption study of ammonia removal from synthetic/real wastewater using ion exchange resins and zeolites

2020· article· en· W3001327070 on OpenAlexafffund
Farooq Al–Sheikh, Carol Moralejo, Mark Pritzker, William A. Anderson, Ali Elkamel

Bibliographic record

VenueSeparation Science and Technology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryAdsorptionWastewaterAmmoniaIon-exchange resinIon exchangeZeoliteInorganic chemistryNuclear chemistryPulp and paper industryIonWaste managementOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

The presence of ammonia in wastewater from industry activities is an important environmental issue; therefore, an adsorption process is one viable alternative process that can be used to reduce concentrations, and accordingly, 10 resins and 6 zeolites were tested for the removal of ammonia from real wastewater (3.8 to 8 mg/L NH3 − N) containing other cations. In subsequent tests, the performance of the most promising adsorbents (four resins & two zeolites) was further characterized using isotherms and kinetic experiments. Adsorbent equilibrium capacities in the range of 0.2 to 0.4 mg/g were determined for ammonia concentrations of approximately 1 mg/L.

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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.027
GPT teacher head0.279
Teacher spread0.252 · 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

Citations39
Published2020
Admission routes2
Has abstractyes

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