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Record W2168693435 · doi:10.1021/bp0343716

[no title]

2004· article· en· W2168693435 on OpenAlex
Yinhua Wan, Raja Ghosh, Zhanfeng Cui

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

VenueBiotechnology Progress · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein purification and stability
Canadian institutionsMcMaster University
Fundersnot available
KeywordsUltrafiltration (renal)FractionationChromatographyHuman serum albuminMembraneIonic strengthChemistrySalt (chemistry)Serum albuminPhase (matter)SelectivityAlbuminAnalytical Chemistry (journal)BiochemistryAqueous solution

Abstract

fetched live from OpenAlex

The fractionation of the plasma proteins human serum albumin (HSA) and human immunoglobulins (HIgG) using the combination of two newly developed techniques, pulsed sample injection technique and carrier phase ultrafiltration (CPUF), is discussed in this paper. The effects of pH and ionic strength on the transmission of a single protein (i.e., either HSA or HIgG) through 100 and 300 kDa MWCO polyethersulfone (PES) membranes were quantified using the pulsed sample injection technique. The experimental results thus obtained suggested that it would be possible to fractionate these proteins by optimizing the solution pH and ionic strength. With 100 and 300 kDa PES membranes, effective separation of HSA and HIgG was achieved by CPUF using suitable conditions, i.e., pH 4.7 and low salt concentration. The fractionation of HSA and HIgG by "reverse selectivity" using 300 kDa membranes was also examined.

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 categoriesMeta-epidemiology (narrow)
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 score0.041
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.008
GPT teacher head0.252
Teacher spread0.244 · 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