Riflessioni sullo stato di “abbandono” dei popolamenti forestali: bene auspicato o paventata negatività?
Bibliographic record
Abstract
References Andreatta G., 2022a - Il paradosso della carne a "chilometro zero" e del carbone a "chilometri diecimila". Silvae.it - Rivista tecnico-scientifica e ambientale dell'Arma dei Carabinieri; https://www.carabinieri.it/media---comunicazione/silvae/la-rivista/aree-tematiche/energie-alternative/il-paradosso-della-carne-a-chilometro-zero-e-del-carbone-a-chilometri-diecimila Andreatta G., 2022b - La ricerca del punto di equilibrio per la gestione selvicolturale dei popolamenti forestali. L'Italia Forestale e Montana, 77 (2): 89-96. https://doi.org/10.36253/ifm-1710 Ciancio O., 2011 - Systemic silvicolture: philosophical, epistemological, methodological aspects. L'Italia Forestale e Montana, 66 (3): 181-190; https://doi.org/10.4129/ifm.2011.3.01 Ciancio O., 2014 - Storia del pensiero forestale. Selvicoltura, filosofia, etica. Rubbettino Editore, Soveria Mannelli (CZ), 546 p. Ciancio O., Nocentini S., 2011 - Biodiversity conservation and systemic silviculture: concepts and applications. Plant Biosystems, 145 (2): 411-418; https://doi.org/10.1080/11263504.2011.558705 Nocentini S., 2019 - La gestione del bosco come sistema biologico complesso: una questione di teoria e di metodo. L'Italia Forestale e Montana, 74 (1): 11-23; https://doi.org/10.4129/ifm.2019.1.02 Nocentini S., Buttoud G., Ciancio O., Corona P., 2017 - Managing forests in a changing world: the need for a systemic approach. A review. Forest System, 26: 1-15; https://doi.org/10.5424/fs/2017261-09443 Nocentini S., Ciancio O., Portoghesi P., Corona P., 2021 - Historical roots and the evolving science of forest management under a systemic perspective. Canadian Journal of Research, 51: 163-171; https://doi.org/10.1139/cjfr-2020-0293
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".