L’or, la cire et l’oeuf. La couleur jaune comme tertium comparationis en français médiéval
Bibliographic record
Abstract
In this paper, we analyze the intensive comparisons applied to medieval French adjectives with the meaning ‘yellow’ or with closely related meanings. On the basis of the concept of collocation defined by the Explanatory and Combinatorial Lexicology (Meaning- Text Theory), we study the second terms of these comparisons in successive sections. A first section presents the concept of collocation. The second section is dedicated to the second term of comparison ‘gold’. The third section deals with the term ‘wax’ and the fourth section deals with the term ‘egg yolk’. A fifth section regroups other less frequent second terms of the comparison, such as ‘kite spawn’, ‘oriole feather’ or ‘Spanish broom’. This paper is integrated in the COLINDANTE research project (I+D+i PID2019-104741GB-100, Ministry of Science and Innovation, Spain) and is part of a series of works that describe intensive comparisons based on the names of colors in medieval French.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 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 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".