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Record W2278289261 · doi:10.1021/acs.analchem.5b04915

A Colloidal Stability Assay Suitable for High-Throughput Screening

2016· article· en· W2278289261 on OpenAlexafffund
Carla Abarca, M. Monsur Ali, Songtao Yang, Xiaofei Dong, Robert Pelton

Bibliographic record

VenueAnalytical Chemistry · 2016
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsMcMaster University
FundersComisión Nacional de Investigación Científica y TecnológicaNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryThroughputHigh-throughput screeningChromatographyColloidNanotechnologyBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

A library of 32 polystyrene copolymer latexes, with diameters ranging between 53 and 387 nm, was used to develop and demonstrate a high-throughput assay using a 96-well microplate platform to measure critical coagulation concentrations, a measure of colloidal stability. The most robust assay involved an automated centrifugation-decantation step to remove latex aggregates before absorbance measurements, eliminating aggregate interference with optical measurements made through the base of the multiwell plates. For smaller nanoparticles (diameter <150 nm), the centrifugation-decantation step was not required as the interference was less than with larger particles. Parallel measurements with a ChemiDoc MP plate scanner gave indications of aggregation; however, the results were less sensitive than the absorbance measurements.

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)0.002
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.259
Teacher spread0.235 · 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
GenreMethods

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

Citations6
Published2016
Admission routes2
Has abstractyes

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