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Record W2793283829 · doi:10.1002/cptx.38

Use of Human Embryoid Bodies for Teratology

2018· article· en· W2793283829 on OpenAlexaff
Anthony Flamier, Supriya Singh, Theodore P. Rasmussen

Bibliographic record

VenueCurrent Protocols in Toxicology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsTeratologyEmbryoid bodyBiologyEmbryonic stem cellPregnancyGeneticsFetus

Abstract

fetched live from OpenAlex

Human birth defects are relatively common and can be caused by exposure to environmental teratogens or to pharmaceuticals with teratogenic activities. Human embryonic stem cells (hESCs), by virtue of their pluripotent nature, provide an excellent cellular platform for teratogen detection and risk assessment. This unit describes detailed protocols for the preparation and validation of highly pluripotent hESCs, the production of large quantities of aggregated multicellular spheroids composed of hESCs, and these spheroids' differentiation into embryoid bodies (EBs). EBs contain a variety of cells of endodermal, ectodermal, and mesodermal origin and can be subjected to compound exposure in vitro. Hence, they are useful for the detection of chemicals with teratogenic activities. Beyond describing protocols to assemble and culture EBs, this unit details methods to exploit the EB system for teratological assessment. In addition, strategies to distinguish compounds with bona fide teratogenic activity versus simple toxicity are discussed. © 2018 by John Wiley & Sons, Inc.

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 score0.186
Threshold uncertainty score0.628

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 studies0.0000.001
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 head0.125
GPT teacher head0.431
Teacher spread0.306 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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