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Record W2128338233 · doi:10.1186/gb-2007-8-6-r113

LongSAGE profiling of nine human embryonic stem cell lines

2007· article· en· W2128338233 on OpenAlexafffund
Martin Hirst, Allen Delaney, Sean A Rogers, Angelique Schnerch, Deryck R. Persaud, Michael D. O’Connor, Thomas Zeng, Michelle Moksa, Keith Fichter, Diana Mah, Anne Go, Ryan D. Morin, Ágnes Baross, Yongjun Zhao, Jaswinder Khattra, Anna‐Liisa Prabhu, Pawan Pandoh, Helen McDonald, Jennifer Asano, Noreen Dhalla, Kevin Ma, Stephanie J. Lee, Adrian Ally, Neil Chahal, Stephanie Menzies, Asim Siddiqui, Robert A. Holt, Steven J.M. Jones, Daniela S. Gerhard, James A. Thomson, Connie J. Eaves, Marco A. Marra

Bibliographic record

VenueGenome biology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsBC Cancer Agency
FundersU.S. Public Health ServiceMonash UniversityGenome British ColumbiaDepartment of Obstetrics, Gynecology and Reproductive Sciences, University of PittsburghMichael Smith Health Research BCStem Cell NetworkGenome CanadaNational Cancer InstituteNational Institutes of HealthU.S. Department of Health and Human Services
KeywordsEmbryonic stem cellInduced pluripotent stem cellBiologyStem cellCell biologyCell cultureComputational biologyMolecular biologyGeneticsGene

Abstract

fetched live from OpenAlex

To facilitate discovery of novel human embryonic stem cell (ESC) transcripts, we generated 2.5 million LongSAGE tags from 9 human ESC lines. Analysis of this data revealed that ESCs express proportionately more RNA binding proteins compared with terminally differentiated cells, and identified novel ESC transcripts, at least one of which may represent a marker of the pluripotent state.

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 score0.006
Threshold uncertainty score0.423

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 head0.017
GPT teacher head0.294
Teacher spread0.276 · 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

Citations28
Published2007
Admission routes2
Has abstractyes

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