Bibliographic record
Abstract
In September 1269, an aging and somewhat embittered king James the Conqueror found himself cast up on the shores of southern France. Against the wishes of his sons and subjects (most of whom stayed sensibly at home), James had decided to relive his past glories by leading a small crusading fleet to the Holy Land. Unfortunately, the storms and contrary winds of an early Mediterranean autumn forced abandonment of his plans as a result of seasickness long before contact could be made with the “infidel.” In his Llibre dels fets James later recalled the day he was blown ashore: And while we were in that port [Agde, about a day's march south-west of Montpellier], our head cook said to us that outside in a boat were Fra Pere Cenra and Fra Ramon Martí, who had arrived from Tunis. And they asked what ship it was and they said to them that it was the ship of the king, who had returned because of the bad weather. And we thought that they would wait there for us, but they went from there to Montpellier. James' memory was inaccurate on at least one point. The Dominican friar Peter Cendra (also Cenra, lat. Cineris ) had died many years previously, and it was his brother Francis – then prior of St. Catherine's in Barcelona – who so rudely neglected his king at Agde. Nevertheless, the incident made an impression and stuck in James' mind.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.039 | 0.006 |
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".