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Record W2006692006 · doi:10.1179/174329409x446287

Electrochemical deposition of composite biopolymer films

2009· article· en· W2006692006 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSurface Engineering · 2009
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAlginic acidMaterials scienceThermogravimetric analysisFourier transform infrared spectroscopyChemical engineeringDeposition (geology)BiopolymerComposite numberDifferential thermal analysisBiocompatibilityAdsorptionNuclear chemistryPolymerComposite materialChemistryOrganic chemistryMetallurgyDiffraction

Abstract

fetched live from OpenAlex

Composite films of alginic acid–hyaluronic acid and alginic acid–heparin were deposited by electrochemical method for the surface modification of conductive substrates. Obtained films were studied by SEM, thermogravimetric analysis (TGA), differential thermal analysis (DTA) and Fourier transform infrared spectroscopy (FTIR). The deposition yield increased with increasing concentration of hyaluronate and heparin in the alginate solutions. The results of deposition yield measurements coupled with the results of TGA and DTA studies showed the possibility of the formation of deposits of different composition. These results are in a good agreement with the FTIR data, which revealed characteristic adsorption peaks of hyaluronic acid and heparin for the composite films. Film thickness was varied in the range of 0–10 μm by the variation of the deposition time at a constant deposition voltage. Obtained films can be used for the surface modification of biomedical implants with improved biocompatibility.

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 score0.002
Threshold uncertainty score0.540

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 head0.006
GPT teacher head0.229
Teacher spread0.222 · 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