Étude comparée de quatre logiciels de gestion de références bibliographiques libres ou gratuits
Bibliographic record
Abstract
Cet article résulte d’une réflexion sur les outils de gestion de références bibliographiques, particulièrement ceux proposés sous une forme libre ou gratuite. Depuis 2007, l’interaction des outils de rédaction avec les éditeurs bibliographiques évolue rapidement, mais par le passé, les logiciels libres ont pu souffrir de la comparaison en termes d’ergonomie ou d’usage avec l’offre propriétaire. Ce panorama fonctionnel, et technique approfondi des solutions libres ou gratuites actuelles résulte de la comparaison des logiciels JabRef, Mendeley Desktop, BibDesk et Zotero menée en janvier 2012 par deux enseignants chercheurs au sein de l’Institut national français des techniques de la documentation (INTD).
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 | 0.015 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".