Inventorying the Manuscripts of Venice’s Biblioteca Nazionale Marciana (Before and) After Zanetti Notes on the Zanetti Draft, the Zanetti Appendices, and the ‘New’ and ‘Present’ Appendices to Zanetti
Bibliographic record
Abstract
The present study traces the documented history of cataloguing the manuscript fonds of Venice’s Biblioteca Marciana, and in particular the Latin and Romance manuscript fonds, drawing from official sources (such as Anton Maria Zanetti’s published catalogues [1740‑41] and the Appendice a Zanetti), from published and unpublished pre-Zanetti sources, and from published and, most importantly, unpublished post-Zanetti sources. A particular inventory of early Marciana manuscripts not described in the Zanetti catalogues is brought to light and compared with entries in the later Appendice a Zanetti. Additional findings on cataloguing the French corpus are revealed.
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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 | 0.001 | 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 | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".