ResearchScope - A Federated Search Service for Irish Open Access Research
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
ResearchScope\nTo mark open access week 2009, (See: http://www.openaccessweek.org/ ),WIT Libraries have launched a federated harvesting and discovery service called ResearchScope. ResearchScope is a national portal designed to raise the profile of Open Access research in Ireland - by making it more visible. \nIt works by harvesting information from research repositories, which present their records in an agreed standard called OAI-DC. By pulling this information together in to one index and re-presenting them via ResearchScope as well as the original home repositories, the information is made more visible to web search engines. It is worth noting that ResearchScope itself presents the aggregated data in this way and it can therefore be indexed itself by other services. See http://www.repository.wit.ie/index.php/oai?verb=ListSets\nResearchScope is based on existing software produced by the Public Knowledge Project, a Canadian group based in Simon Frasier University. (See: http://pkp.sfu.ca/ ) With minor modifications to the layout and the addition of a graphical 'word cloud' search, ( See: http://www.quintura.com/ )we have produced an appealing and useful single point of access to open access research in Ireland. We would to organically incorporate tools and services as time goes on.\nThe widespread global interest in the movement toward open, public access to scholarly research results is steadily gaining momentum and ResearchSchope is also an attempt to broaden awareness/understanding of Open Access to research, on the part of research funders, the Irish higher education community and the general public - who pay for this research with their hard-earned taxes. \nSee: http://researchscope.net/
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.256 | 0.045 |
| Open science | 0.027 | 0.046 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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