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Record W1972170454 · doi:10.1002/pssa.200674380

Using an oxidized porous silicon interferometer for determination of relative protein binding affinity through non‐covalent capture probe immobilization

2007· article· en· W1972170454 on OpenAlexaff
Michael P. Schwartz, Christine Yu, Sara D. Alvarez, Benjamin Migliori, Denis Godin, Lin Chao, Michael J. Sailor

Bibliographic record

Venuephysica status solidi (a) · 2007
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsCovalent bondBovine serum albuminChemistryPorous siliconAdsorptionProtein AChromatographyTungstenProtein GSiliconAntibodyOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Abstract An oxidized porous Si interferometer was used to measure binding of immunoglobulin G (IgG) to an immobilized protein A capture probe. Protein A was non‐covalently immobilized on a thermally oxidized porous Si (PSiO2) sample and exposed to IgG originating from different species. The resulting order of IgG affinity toward the protein A‐coated surface (human > rabbit ≫ sheep IgG) agrees with previous inhibition studies for protein A/IgG binding. No signal change was observed when a protein A coated sample was exposed to bovine serum albumin (BSA), demonstrating that the adsorbed sensing layer sufficiently coats the PSiO2 surface to prevent non‐specific binding. This strategy is excellent for qualitative measurements of protein binding affinity because it is label‐free, requires minimal sample preparation, and can be implemented using an inexpensive CCD‐based spectrometer coupled to a tungsten lamp. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

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)0.001
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.325
Teacher spread0.280 · 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

Citations31
Published2007
Admission routes1
Has abstractyes

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