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
Summary VIVO [Pronunciation: vee-voh] is member-supported, enterprise open source software and an ontology for representing scholarship. VIVO supports recording, editing, searching, browsing and visualizing scholarly activity. VIVO encourages research discovery, expert finding, network analysis and assessment of research impact.<br> VIVO is easily extended to support additional domains of scholarly activity. VIVO uses an ontology to represent people, papers, grants, projects, datasets, resources, and other elements of research and scholarship as linked open data. The ontology can be used to create RDF that can be loaded into VIVO. VIVO RDF data is easily exported for use in other applications. VIVO includes Vitro, a domain-free engine for managing linked open data, the JFact reasoner, SolR for search, SPARQL query, Jena as a triple store, supporting both TDB and SDB on MySQL, uses D3 for visualizations, and provides multiple APIs, including Triple Pattern Fragments for rapid remote access to specified data. Using VIVO, organizations can represent the activities and accomplishments of their scholars as linked open data, and share that data with others. Acknowledgements The authors wish to acknowledge the foundational work done on VIVO, and VIVO concepts by the team at the Mann Agricultural Library, Cornell University, led by Jon Corson-Rikert. The authors also wish to acknowledge NIH grant 1U24RR029822-01 to the first author, which funded the work of more than 120 co-investigators in the further development of the VIVO software, and NIH grant xxxxxxx to Dr. Melissa Haendel of Oregon Health Science University which funded significant advances in the VIVO Integrated Semantic Framework, which VIVO uses to represent scholarship. Finally, the authors wish to acknowledge the many hundreds of members of the VIVO community around the world, who volunteer their time and effort to advance the art of representing scholarship as linked open data. The work described here builds on the work of many others.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 0.069 |
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