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Record W2028117650 · doi:10.1089/adt.2010.0346

The Zebrafish: A Powerful Platform for <i>In Vivo</i> , HTS Drug Discovery

2011· review· en· W2028117650 on OpenAlexaff
Chris Delvecchio, Jens Tiefenbach, Henry M. Krause

Bibliographic record

VenueAssay and Drug Development Technologies · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsZebrafishDanioDrug discoveryComputational biologyBiologyDrug developmentDrugComputer sciencePipeline (software)VertebrateBioinformaticsPharmacologyGeneticsGene

Abstract

fetched live from OpenAlex

The zebrafish (Danio rerio) is an emerging vertebrate model for drug discovery that permits whole animal drug screens with excellent throughput, combined with ease of use and low cost. This review will begin with a discussion on the background, suitability, and advantages of this vertebrate model system and then, citing specific examples, will describe the utility of zebrafish at specific stages in the drug development pipeline. We will end with a synopsis of recent drug screens based on morphological disruptions, genetic disease models, fluorescent markers, behavioral changes, and specific targets. The numerous advantages of this whole animal approach provide new promise for the discovery of safe, specific, and powerful new drugs.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.023
GPT teacher head0.295
Teacher spread0.272 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations112
Published2011
Admission routes1
Has abstractyes

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