OntoFox: web-based support for ontology reuse
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Ontology development is a rapidly growing area of research, especially in the life sciences domain. To promote collaboration and interoperability between different projects, the OBO Foundry principles require that these ontologies be open and non-redundant, avoiding duplication of terms through the re-use of existing resources. As current options to do so present various difficulties, a new approach, MIREOT, allows specifying import of single terms. Initial implementations allow for controlled import of selected annotations and certain classes of related terms. FINDINGS: OntoFox http://ontofox.hegroup.org/ is a web-based system that allows users to input terms, fetch selected properties, annotations, and certain classes of related terms from the source ontologies and save the results using the RDF/XML serialization of the Web Ontology Language (OWL). Compared to an initial implementation of MIREOT, OntoFox allows additional and more easily configurable options for selecting and rewriting annotation properties, and for inclusion of all or a computed subset of terms between low and top level terms. Additional methods for including related classes include a SPARQL-based ontology term retrieval algorithm that extracts terms related to a given set of signature terms and an option to extract the hierarchy rooted at a specified ontology term. OntoFox's output can be directly imported into a developer's ontology. OntoFox currently supports term retrieval from a selection of 15 ontologies accessible via SPARQL endpoints and allows users to extend this by specifying additional endpoints. An OntoFox application in the development of the Vaccine Ontology (VO) is demonstrated. CONCLUSIONS: OntoFox provides a timely publicly available service, providing different options for users to collect terms from external ontologies, making them available for reuse by import into client OWL ontologies.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it