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Record W2969220760 · doi:10.1080/01496395.2019.1655457

Ammonia removal from real wastewater using a LEWATIT S 108 H resin: A batch process and fixed-bed column

2019· article· en· W2969220760 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSeparation Science and Technology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryAdsorptionWastewaterFreundlich equationAmmoniaColumn (typography)ChromatographyIon-exchange resinSelectivityPulp and paper industryInorganic chemistryOrganic chemistryCatalysisEnvironmental engineeringEnvironmental science

Abstract

fetched live from OpenAlex

The ammonia component represents a sizable portion of pollutants in mining wastewater (MW) and because of its high selectivity toward ammonia, a LEWATIT resin was tested in the batch adsorption using different masses with 22.7 mg/L NH3 − N and in the continuous adsorption using two fixed-bed columns. Also, resin regeneration was achieved using diluted HCl. The results show the adsorption follows Freundlich isotherm in the batch study and was characterized by both the Bohart–Adams and Thomas models in the fixed-bed column. HCl can be used to regenerate LEWATIT with efficiency 40% and 70% for the small and large column, respectively.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.274
Teacher spread0.264 · 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