Bibliographic record
Abstract
In this article, the author proposes that the physiognomy of the painter Jacques-Louis David should be recognized in a Portrait d’homme belonging to the Musée Bonnat in Bayonne. This comparison is first of all based on the fairly close resemblance that exists between this head, painted by Nicolas-Bernard Lépicié (1735-84), and reliable, known effigies of David, such as his self-portrait of 1794 in the Louvre. It must be said that the quite particular characteristics of the painter have always facilitated his identification. David, in fact, had the left part of his face deformed by a swelling, the outcome of a wound received during his youth. This physical characteristic is present in Lépicié's sitter, along with other distinctive traits of the painter, such as his broad, straight brow, his circumflex-shaped eyebrows, and finally, the slightly bulging tip of his nose. We know, moreover, that the two painters each occupied a studio in the Louvre between the years 1782 and 1784. It may be that this “neighbourhood” provided the occasion for them to cultivate a certain relationship and ties of which the Bayonne canvas now constitutes the only evidence.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".