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Sulfated cellulose thin films with antithrombin affinity

2009· article· en· W2072500823 on OpenAlexaff
Ringo Grombe, M.-F. Gouzy, Uwe Freudenberg, W. Pompe, Stefan Zschoche, Frank Simon, K.‐J. Eichhorn, Andreas Janke, Brigitte Voit, Carsten Werner

Bibliographic record

VenueeXPRESS Polymer Letters · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProteoglycans and glycosaminoglycans research
Canadian institutionsUniversity of TorontoUniversity of New Brunswick
FundersLeibniz-GemeinschaftLeibniz-Institut für Polymerforschung DresdenBundesministerium für Bildung und Forschung
KeywordsMaterials scienceCelluloseAntithrombinSulfationPolymer scienceChemical engineeringBiochemistryChemistryHeparinEngineering

Abstract

fetched live from OpenAlex

Cellulose thin films were chemically modified by in situ sulfation to produce surfaces with anticoagulant characteristics.Two celluloses differing in their degree of polymerization (DP): CEL I (DP 215-240) and CEL II (DP 1300-1400) were tethered to maleic anhydride copolymer (MA) layers and subsequently exposed to SO3•NMe3 solutions at elevated temperature.The impact of the resulting sulfation on the physicochemical properties of the cellulose films was investigated with respect to film thickness, atomic composition, wettability and roughness.The sulfation was optimized to gain a maximal surface concentration of sulfate groups.The scavenging of antithrombin (AT) by the surfaces was determined to conclude on their potential anticoagulant properties.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.237
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2009
Admission routes1
Has abstractyes

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