Bibliographic record
Abstract
I n the short interval between his accession and the start of the Asiatic campaign, Alexander suppressed rebellion in the south and unrest on his northern borders – all with terrifying ease. A rapid move into Thessaly silenced the first grumblings of discontent, and in the following year (335 BC) he arrived at the gates of Thebes, dispelling by his very presence rumors of his death in the north. A single act of terror – the destruction of the city and the enslavement of its population – served to impress upon the Greeks the futility of opposition. The Spartans refused to join the League, just as they had after Chaeronea, but theirs was for now a passive resistance. When they did finally attempt to reassert themselves, they found few allies and no military success. SETTING THE STAGE In 334 Alexander's army crossed the Hellespont from Sestos to Abydus on 160 warships and an assortment of cargo craft. That Alexander did not build a boat-bridge was probably a matter of economics – his finances were an ongoing concern at the beginning of the expedition – and the recollection that Xerxes' “chaining” of the Hellespont was regarded as hubristic. Instead he used every symbol in the Panhellenic arsenal. At Dium in Macedonia he staged games in honor of the Muses and the Olympian gods.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".