Bibliographic record
Abstract
References to elephants captured by Alexander up until the battle of the Hydaspes (326 bc ) are awkward to explain, especially given that the beasts, according to the surviving accounts, filled the Macedonian and allied troops with terror in the same engagement. This is problematic if Alexander’s men had already encountered elephants, even if not in the context of a pitched battle. Moreover, analysis of the evidence suggests that Alexander, far from despising elephants, as our sources, and Curtius Rufus in particular, contend, regarded their possession as both politically and militarily important, and decided to incorporate the animals into the Macedonian army on this basis. Les références aux éléphants capturés par Alexandre avant la bataille de l’Hydaspe (326 avant J. C.) sont difficiles à expliquer, d’autant plus que, selon les récits disponibles, les bêtes remplirent de terreur Macédoniens et troupes alliées au cours de ce même affrontement. Cela pose problème si les hommes d’Alexandre avaient déjà rencontré des éléphants, fût-ce dans un contexte autre que celui d’une bataille rangée. De plus, l’analyse des témoignages suggère que, loin de mépriser les éléphants, comme le prétendent nos sources, et en particulier Quinte-Curce, Alexandre considérait leur possession comme importante d’un point de vue à la fois politique et militaire, et décida de ce fait d’incorporer ces animaux dans l’armée macédonienne.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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".