dgarijo/Widoco: WIdoco 1.3.0: Automated changelog section
Bibliographic record
Abstract
This version of Widoco creates an automated changelog section of your ontology. For all classes, properties and data properties, Widoco will calculate the new changes, additions and deletions and present them in a human-readable manner. In order to benefit from this feature, you just have to annotate your ontology with the URI of the previous version. You can use owl:priorVersion, dc:replaces or prov:wasRevisionOf to annotate your ontology (Widoco will only consider one file to compare against). Additional improvements: RDF-a annotations are replaced with JSON-LD snippets. The page is just annotated with schema.org. The rdf-a annotations made it difficult to maintain, and the structured extraction tool provided by Google did not work. With the JSON-LD snippet everything is clearer. The provenance of the page itself is published separately. Now it is possible to generate ONLY the cross reference section of an ontology. Bug fix that led to errors when opening some ontologies like OBI
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.105 | 0.081 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".