Bibliographic record
Abstract
There were many words that you could not stand to hear and finally only the names of places had dignity.-Ernest Hemingway, A Farewell to Arms I couldn't escape it, the monument on the hill.The white pseudo-Roman arch loomed over the streets of the town and the surrounding plateau.I hadn't come to Asiago to visit a memorial to the First World War.My husband and I had driven up from Venice at the urging of an old and dear friend.Over the years we had met up with Mimma on her visits to Edmonton or, more often, when she and her family came down to Venice to see us.So it was only right that this time we made the effort.The distance between Venice and Asiago is short, 122 kilometres, almost nothing for two Western Canadians, yet the place feels isolated and remote.Encircled by towering mountains, the high plateau is a Shangri-la of dense woods, rolling hills, and meadows dotted with bright flowers and clusters of contented, munching cows.Its history, I would learn, is separate and different from that of the rest of Italy, or even the rest of the Veneto.The original inhabitants were the Cimbri, a Germanic people! who spoke (and continued to speak until modern times) a Bavarian dialect.A thousand years later, their heritage survives in the names of places and people, in the Tyrolean cast of the architecture, and in the folklore, with its tales of gnomes and trolls.And most particularly, in the preponderance of tall, blond, and light-eyed citizens, like Mimma's husband or her fifteen-year-old daughter who was already six feet tall.From the Middle Ages to the beginning of the nineteenth century, the high mountains kept out invaders and protected the Cimbri from the competing powers who marauded through the rest of Italy.Significantly, the Regency, the government of the seven towns of the 1 Some historians and archeologists claim the Cimbri migrated from Jutland to Germany in Roman times, moving on a millennium later to the Asiago plateau.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.073 | 0.013 |
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".