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Record W2975051788 · doi:10.1002/cite.201900064

Treatment of Oily and Salty Mining Water by Ceramic Nanofiltration Membranes

2019· article· en· W2975051788 on OpenAlexaboutno aff
Ingolf Voigt, Hans Richter, Marcus Weyd, Kerstin Milew, Roland Haseneder, C Günther, Volker Prehn

Bibliographic record

VenueChemie Ingenieur Technik · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsNanofiltrationMembraneSalt (chemistry)Environmental sciencePotashCeramicPulp and paper industryWater treatmentSalt lakeWaste managementEnvironmental engineeringChemistryGeologyPotassiumEngineering

Abstract

fetched live from OpenAlex

Abstract Ceramic nanofiltration membranes were successfully tested and piloted for the treatment of oily and salty water from oil sand mining in Alberta, Canada. The membranes showed a stable behavior over two years operation. The complete removal of suspended solids as well as the reduction of multivalent ions enable the use of recycle water from tailing ponds to prepare boiler feed water. In high salt concentration like waste water from potash mining a dependency of salt retention on the salt composition and concentration was observed. High MgSO 4 retention even at high salt concentration was achieved.

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 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 score0.008
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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 teacher head, 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

Citations16
Published2019
Admission routes1
Has abstractyes

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