MétaCan
Menu
Back to cohort

Electrophoretic deposition of chitosan–albumin and Alginate–albumin films

2009· article· en· W2079311299 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSurface Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicElectrophoretic Deposition in Materials Science
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrophoretic depositionAlginic acidChitosanElectrophoresisMaterials scienceBovine serum albuminFourier transform infrared spectroscopyThermogravimetric analysisChemical engineeringDeposition (geology)Nuclear chemistryChromatographyChemistryNanotechnologyCoatingBiochemistry

Abstract

fetched live from OpenAlex

Electrophoretic deposition methods have been developed for the fabrication of composite films containing biopolymers and bovine serum albumin (BSA). The mechanism of the deposition of chitosan–BSA films was based on electrophoresis of chitosan and BSA in acidic solutions, and co‐precipitation of insoluble chitosan and BSA in the high pH region at the cathode surface. The mechanism of the anodic deposition of alginic acid–BSA films was based on electrophoresis of alginate and BSA in basic solutions and precipitation of insoluble alginic acid and BSA in the low pH region at the anode surface. The deposition yield measurements and scanning electron microscopy investigations showed that the amount of the deposited material can be controlled by variation of the deposition time. Uniform films with thickness of 0–15 μm were obtained on conductive substrates. The films were studied by thermogravimetric analysis, differential thermal analysis and Fourier transform infrared spectroscopy.

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 score0.030
Threshold uncertainty score0.981

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 head0.002
GPT teacher head0.167
Teacher spread0.165 · 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