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Record W4236062438 · doi:10.1038/npre.2009.3635.1

Hematopoietic Cell Types: Prototype for a Revised Cell Ontology

2009· preprint· en· W4236062438 on OpenAlexaff
Anna Maria Masci, Bali Pulendran, Terrence F. Meehan, Richard H. Scheuermann, Penelope A. Morel, Qing Yao, Anastasia Nijnik, Martin S. Zand, Chris Mungall, Alexander D. Diehl, Alison D. Augustine, Judith A. Blake, Lindsay G. Cowell, Elizabeth S. Gold, Bjoern Peters, Timothy A. Gondré-Lewis

Bibliographic record

VenueNature Precedings · 2009
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiomedical Text Mining and Ontologies
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Allergy and Infectious DiseasesNational Human Genome Research Institute
KeywordsOntologyComputer scienceProcess ontologyOpen Biomedical OntologiesOntology-based data integrationSuggested Upper Merged OntologyGene ontologyUpper ontologyStructuringHematopoietic cellRepresentation (politics)Computational biologyInformation retrievalHaematopoiesisChemistryBiologyGeneStem cellBiochemistryCell biologySemantic Web

Abstract

fetched live from OpenAlex

Abstract The Cell Ontology (CL) aims for the representation of in vivo and in vitro cell types from all of biology. Although the CL is a reference ontology of the OBO Foundry, it requires extensive revision to bring it up to current standards for biomedical ontologies, both in its structure and its coverage of various subfields of biology. A recent workshop sponsored by NIAID on hematopoietic cell types in the CL addressed both issues. The section of the ontology dealing with hematopoietic cells was extensively revised, and plans were set for structuring these cell type terms as cross-products with logical definitions built from relationships to external ontologies, such as the Protein Ontology and the Gene Ontology. The methods and improvement to the CL in this area represent a paradigm for improvement of the whole of the ontology over time.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0040.001
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 head0.011
GPT teacher head0.291
Teacher spread0.280 · 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
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

Citations0
Published2009
Admission routes1
Has abstractyes

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