An archive for the history of limnology at Verbania Pallanza in the Italian Lake District
Bibliographic record
Abstract
Since 2010, work has been underway to curate and catalogue the historical documentation archive of the Verbania Pallanza section of the CNR Institute for Research on Waters, located on the shores of Lake Maggiore in the Italian Lake District. This laboratory was established during the first decade of the 1900s with the work of Marco De Marchi, and research activities intensified from 1938 onwards with the foundation of the Italian Institute of Hydrobiology. The curation of the archives dating from these earliest times to the present has been done with professional archivist technicians from the Archival Superintendence and in collaboration with researchers from the Institute. The archived documents include those from the first phase of the organization of the Institute, as well as those derived from scientific and administrative activities and exchanges with the Ministry of Education. The documents also cover activities at a second section of the Institute, located in an ancient historical residence in Varenna, on the shores of Lake Como. The archive has a photographic section, which includes a series of photographic glass plates, digitized to allow for current use, containing photos of the Institute's environments and laboratories at different times through its history. A third section of the archive consists of around 50 interviews with aquatic scientists on topics relating to research projects carried out in the past. A further section concerns the recording of about 150 seminars on environmental research carried out in the institute between 2015 and 2020. The main research topics considered concern physical, chemical and biological limnology, with particular attention to Lake Maggiore, Lake Orta (severely polluted due to industrial waste), and high-altitude lakes in the Alps. The Institute also houses a library dedicated to environmental issues and some miscellaneous papers by the most important scholars of freshwater science in Italy, with publications starting from the second half of the nineteenth century. Other collections of archival interest are a museum of field and laboratory instruments, and a collection of biological samples, mainly plankton, collected in various Italian lakes.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.012 |
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".