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Record W3167777255 · doi:10.1080/00032719.2021.1932969

Determination of β-Estradiol by Surface-Enhance Raman Spectroscopy (SERS) Using a Surface Imprinted Methacrylate Polymer on Nanoporous Biogenic Silica

2021· article· en· W3167777255 on OpenAlexaff
Samuel M. Mugo, Weihao Lu

Bibliographic record

VenueAnalytical Letters · 2021
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsMacEwan University
Fundersnot available
KeywordsNanoporousChemistryMolecularly imprinted polymerDetection limitSurface-enhanced Raman spectroscopyPolymerMethacrylateMolecular imprintingSubstrate (aquarium)Methyl methacrylateRaman spectroscopyChemical engineeringRaman scatteringNuclear chemistryChromatographySelectivityMonomerOrganic chemistry

Abstract

fetched live from OpenAlex

A phytoplankton derived nanoporous biogenic silica (BS) scaffold grafted with polymethacrylate β-estradiol molecularly imprinted polymers (MIP) film (MIP@BS) is reported as a selective platform for the determination of β-estradiol using surfaced-enhanced Raman scattering (SERS). The biogenic silica nanoparticles provided high surface area support for the MIP while serving as an active signal enhancement substrate for SERS. The MIP@BS platform demonstrated an excellent linear response (R2 = 0.9996) between 0.1 and 4 ng/mL of β-estradiol standards. The limit of detection (LOD) for the MIP@BS SERS sensor for β-estradiol was 0.073 ng/mL. The MIP@BS SERS sensors were successfully evaluated for the determination of β-estradiol in milk, while demonstrating good stability and reusability.

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)0.000
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 score0.008
Threshold uncertainty score0.686

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 head0.016
GPT teacher head0.277
Teacher spread0.261 · 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.

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

Citations14
Published2021
Admission routes1
Has abstractyes

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