Bibliographic record
Abstract
Sometime in the last three decades of the thirteenth century, two medieval scribes sat down to write the melody for the song ‘Pour conforter ma pesance’ by Thibaut IV count of Champagne and king of Navarre, then some thirty years deceased. The one we may call scribe T was writing in the Artois region of France while scribe O was located further south-west, most likely Burgundy or the Isle de France. Despite their geographic distance, these two readings are remarkably similar in pitch, something which we might expect given the relative closeness of these scribes to Thibaut's time. But this is not so for their rhythmic interpretations of Thibaut's melody. Scribe O, who has a decided tendency to interpret trouvère songs rhythmically by indicating long and short values, has here abstained from doing so (example 1.1), while scribe T, who elsewhere does not give rhythmic values, has done so in this case (example 1.2); his reading clearly alternates long and short values, creating a rhythmic pattern called a ‘mode’ (modus) by medieval theorists. For some reason, for this particular song, both music scribes decided to change their habits, switching rhythmic camps, so to speak.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".