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Record W2047964782 · doi:10.1517/17460441.3.11.1267

Scintillation proximity assay in lead discovery

2008· article· en· W2047964782 on OpenAlexaff
Xavier Khawaja, John Dunlop, Dianne Kowal

Bibliographic record

VenueExpert Opinion on Drug Discovery · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsDrug discoveryLead (geology)Computational biologyScintillationBiologyComputer scienceBioinformaticsTelecommunications

Abstract

fetched live from OpenAlex

BACKGROUND: Scintillation proximity assay (SPA) is a homogeneous scintillant bead-based platform for the measurement of biological processes and plays an important role in the identification of active chemical entities in drug discovery. OBJECTIVE: The design and development of solid-phase SPA approaches are examined and compared with alternative non-radiometric fluorescence-based technologies. METHODS: This review provides background on the principle of SPA and its application to biomolecular interactions from a variety of biological sources. CONCLUSION: The SPA approach is well suited to the demands of commercial high volume automation and assay miniaturization for target-based high-throughput screening campaigns on synthetic and natural product libraries as well as for benchtop characterization and confirmation studies. In the near future, innovations in the way SPA and fluorescence-based screening strategies are multiplexed will improve our comprehensive understanding of cellular system biology and dramatically advance the lead discovery process for the treatment of complex target-related disorders.

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)0.004
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.017
GPT teacher head0.303
Teacher spread0.286 · 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

Citations9
Published2008
Admission routes1
Has abstractyes

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