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Record W2160218141 · doi:10.1002/cjce.20501

The extraction of lactic acid by emulsion type of liquid membranes using alamine 336 in escaid 100

2011· article· en· W2160218141 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsDiluentStripping (fiber)ChemistryExtraction (chemistry)Pulmonary surfactantKeroseneEmulsionMembraneLactic acidAqueous solutionChromatographyAqueous two-phase systemHeptaneTolueneNuclear chemistryOrganic chemistryMaterials scienceBiochemistry

Abstract

fetched live from OpenAlex

Abstract The extraction of lactic acid from aqueous solutions through an emulsion liquid membrane containing Alamine 336 as carrier was investigated. The influence of mixing speed, diluent type, surfactant concentration, extractant concentration, feed solution pH, stripping concentration, phase ratio, and feed concentration were examined. Liquid membrane consists of a diluent ( n ‐heptane, toluene, kerosene, Escaid 100, and Escaid 200), a surfactant (Span 80) and an extractant (Alamine 336), and Na 2 CO 3 were used as a stripping solution. It is possible to extract 91% of lactic acid from aqueous solutions using Alamine 336 in Escaid 100, as an extractant and a diluent 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 score0.004
Threshold uncertainty score0.251

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)0.0000.000

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 head0.026
GPT teacher head0.240
Teacher spread0.214 · 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