D7.6 Data Management System and documentation
Bibliographic record
Abstract
This report presents the main components and functionalities of the Data Management System (DMS) implemented by ARICE. The strategic targets driving this development have been: (i) the need to simplify the original plan to address challenges arising from changes in involved partners during the project; (ii) the need, in a legacy perspective, to adopt technical solutions and schemes sustainable in time, and (iii) to take in to account the last developments, at least at European level, made by organisations that are data aggregators and/or data providers. The last two points are relevant in order to accomplish ARICE project g oals in a very cost -effective way. The use of consolidated software packages in the data management panorama at international level and sustained by large communities (e.g. GEOCAT for GeoNetwork), together with the interaction with EMODnet Physics 1, are th e key pillars ensuring that strategic goals will be achieved.
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 | 0.000 |
| 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 | 0.004 | 0.000 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 teacher head, 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".