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Record W7009483388

Electrochemical and PM-IRRAS studies of the interaction of plasma protein fibrinogen with a biomedical-grade 316LVM stainless steel surface

2007· dissertation· en· W7009483388 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2007
Typedissertation
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFibrinogenBiocompatibilityAdsorptionProtein adsorptionBiomaterialElectrochemistryCorrosionKineticsBlood proteins
DOInot available

Abstract

fetched live from OpenAlex

It is widely accepted that the initial event that significantly influences biocompatibility is the nearly instantaneous adsorption of proteins from biological fluids onto the biomaterial surface. For blood-contacting devices, the complex layer of adsorbed plasma proteins is generally unfavourable and leads to major complications, including thrombus formation, inflammatory tissue responses, and microbial infections. Furthermore, protein interaction with passive films on metallic biomaterial surfaces may contribute to enhanced in vivo corrosion. To gain a better understanding of this phenomenon, the present thesis investigated the fundamental aspects of the interaction of the serum protein fibrinogen with a medical-grade stainless steel 316LVM surface using electrochemical and IR spectroscopy techniques. Aspects of this interaction included the thermodynamics and kinetics of fibrinogen adsorption, the effect of fibrinogen adsorption on the corrosion behavior of 316LVM stainless steel, and the conformational changes of fibrinogen upon its adsorption onto the stainless steel surface.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.297
Teacher spread0.273 · 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.

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

Citations0
Published2007
Admission routes1
Has abstractyes

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