Bibliographic record
Abstract
“Would you be good enough,” our delightful interlocutor inquired eagerly, “to tell me what news there is of Mother Prague, the City of a Hundred Towers?” “It is growing, my friend,” I replied, pleased at his interest, and in a few words outlined to him the prosperous growth of our golden metropolis. “What joyful tidings these are,” the Newt said with undisguised satisfaction. “And are the severed heads of the decapitated Czech nobles still stuck up on the Bridge Tower?” “No, they haven't been for a long time,” I said, somewhat (I admit) taken aback by his question. “That is a great pity,” the Newt observed sympathetically. “That was indeed a precious historical relic. It is a pity crying to high Heaven that so many splendid memorials have perished in the Thirty Years’ War! Unless I am mistaken, the Czech land was then turned into a desert drenched with blood and tears. How fortunate that the genitive of negation did not die out then as well! It says in this book that it is on the point of extinction. I am deeply distressed to learn it, sir.” “So you are fascinated also by our history,” I exclaimed joyfully. “Certainly, sir,” the Newt replied. “Especially by the disaster of the White Mountain and the three hundred years of servitude. I have read a lot about that in this book. No doubt you are very proud of your three hundred years of servitude. That was a great period, sir!” “Yes, a hard period,” I agreed. “A period of oppression and grief.” “And did you groan?” our friend inquired with keen interest. “We groaned, suffering inexpressibly under the yoke of the savage oppressors.” “I am delighted to hear it,” the Newt heaved a sigh of relief. “That is exactly what it says in my book. I am happy to find it is true.…” – Karel Čapek, War with the Newts
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.278 | 0.152 |
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".