Bibliographic record
Abstract
Cleopatra William Shakespeare and Paul Murgatroyd The barge she sat in, like a burnish’d throne, Burn’d on the water; the poop was beaten gold, Purple the sails, and so perfumed, that The winds were love-sick with them, the oars were silver, Which to the tune of flutes kept stroke, and made The water which they beat to follow faster, As amorous of their strokes. For her own person, It beggar’d all description; she did lie In her pavilion, cloth-of-gold of tissue, O’er-picturing that Venus where we see The fancy outwork nature; on each side her Stood pretty dimpled boys, like smiling Cupids, With divers-colour’d fans, whose wind did seem To glow the delicate cheeks which they did cool, And what they undid did. Shakespeare, Antony and Cleopatra, Act II Scene II ceu solium splendens, cymba in qua desidet illa ignivomis flammis fluminis urit aquas. aureola est puppis, perfragrans purpura veli, auraque cuncta calet languida amore fero. palmula et argento pallebat plurima puro; omnis et e calami carmine mota simul. tacta brevi remis, remos cito lympha secuta est, contingi rursus remigio cupiens. illa sub auratis aulaeis aurea fusa; depingi dictis sed satis illa nequit. scis Venerem in tabulis naturam vincere vafris: ast ab regina vincitur illa Venus. sunt pueri pulchra facie parvisque lacunis. quisque habitu nitido nempe videtur Amor. subrident semper varias vibrantque tabellas. hi circum dominam stant teneram teneri. illius os perque hos ventis frigetque caletque; infectum faciunt quod pariter faciunt. [End Page 71] Paul Murgatroyd McMaster University murgatro@mcmaster.ca Copyright © 2009 Mouseion
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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".