Bibliographic record
Abstract
Open Source Semantic Web Ontology (OSSWO) is the application of my Open Source Culture an Open Internet historiographic research to the secure operational development (DevSecOps) of a first ontological alignment World Wide Web Consortium (W3C) standard. It is being drafted through my several years with its Credible Web workgroup along the International Telecommunications Union (ITU), Open Data Institute (ODI), Creative Commons (CC) Open Education Platform, National Aero Spacial Agency (NASA) Open Science Initiative (OSI). Its first compilation happened during the United Nations World Summit on the Information Society (WSIS) and vastly reviewed to my participation at the United Nations Education Science Culture Organization (UNESCO) University Twinning and Networking Programme (UNITWIN) Cyberspace Culture Summit with the purpose to establish rule of law (RoL) regulatory compliance for my Open Justice Ontology (OJO).
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.016 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.013 |
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; both teacher heads agree on what is shown here.
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".