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Record W2022153942 · doi:10.1155/2015/139041

Modeling Breakthrough Curves of Citric Acid Adsorption onto Anionic Resins in an Aqueous Solution

2015· article· en· W2022153942 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

VenueJournal of Engineering · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCitric acidAqueous solutionAdsorptionIon-exchange resinIon exchangeChemistryApproximation errorThermodynamicsMaterials scienceMathematicsIonApplied mathematicsInorganic chemistryOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Breakthrough curves for citric acid adsorption from aqueous solution onto ion-exchange resin at 20, 35, and 55°C have been investigated. To predict breakthrough curves, three mathematical models have been analyzed based on the values of the least square method parameters, Durbin-Watson test, and mean relative percent error and, finally, appropriate models have been achieved. Models are in good agreement with experimental data based on the results. To examine models reliabilities and accuracy, models have been compared by various breakthrough curve data obtained by other investigators. The results show appropriate agreement and in some cases regression errors have been reduced to less than 1.0 percent.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.246
Teacher spread0.218 · 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