The Arthur of Medieval Latin literature : the development and dissemination of the Arthurian legend in Medieval Latin
Bibliographic record
Abstract
Section One: The Seeds of History and Legend 1) The Chroniclers of Early Britain NICK HIGHAM, University of Manchster 2) Arthur in Early Saints' Lives ANDREW BREEZE, Departamento de Linguistica Hispanica y Lenguas Modernas, Pamplona, Spain Section Two: Geoffrey of Monmouth 3) Geoffrey of Monmouth SIAN ECHARD 4) Geoffrey and the Prophetic Tradition JULIA CRICK, University of Exeter Section Three: Chronicles and Romances 5) Latin Historiography after Geoffrey of Monmouth AD PUTTER, University of Bristol 6) Glastonbury EDWARD DONALD KENNEDY, University of North Carolina 7) Romance ELIZABETH ARCHIBALD, University of Bristol Section Four: After the Middle Ages 8) Arthur and the Antiquaries JAMES P. CARLEY, York University, Toronto 3) Geoffrey of Monmouth SIA N ECHARD 4) Geoffrey and the Prophetic Tradition JULIA CRICK, University of Exeter Section Three: Chronicles and Romances 5) Latin Historiography after Geoffrey of Monmouth AD PUTTER, University of Bristol 6) Glastonbury EDWARD DONALD KENNEDY, University of North Carolina 7) Romance ELIZABETH ARCHIBALD, University of Bristol Section Four: After the Middle Ages 8) Arthur and the Antiquaries JAMES P. CARLEY, York University, Toronto
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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 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".