Processi di riconoscimento collettivo dei fenomeni urbani : letture sul patrimonio culturale in Iuav Abroad = Collective acknowledgements of urban Phenomena : Visions on Heritage by Iuav Abroad
Bibliographic record
Abstract
Iuav Abroad Series \nScientific board / Comitato scientifico Alberto Ferlenga \nBenno Albrecht \nEnrico Fontanari \nEmanuela Sorbo \nElisa Brusegan \nQuesto volume presenta gli atti della reunion “Iuav Academics Abroad. Strategie di internazionalizzazione” tenutasi in Aula Tafuri a Palazzo Badoer il 22 marzo 2019 in seno agli eventi dedicati al network \n“Iuav Abroad” della Università Iuav di Venezia in collaborazione con Iuav Alumni \nLe attività promosse sono a cura di Alberto Ferlenga, Benno Albrecht, Enrico Fontanari, Emanuela Sorbo, Elisa Brusegan \nHanno partecipato Gustavo Adolfo Carabajal, Universidad Nacional de Rosario, Rosario (Argentina); Serena Conti, Université Libre de Bruxelles, Bruxelles (Belgio); Maroun Daccache, Lebanese American University, Byblos (Libano); Luca Donner, Canadian University Dubai, Dubai (EAU); Azad Hama, Tishk International University, Erbil (Iraq); Carla Keyvanian Auburn University, Auburn (USA); Silvia Mazzetto, Lebanese American University, Byblos (Libano); Manlio Michieletto, University of Rwanda, Kigali (Ruanda); Francesco Polesello, Azm University, Tripoli (Libano); Alessandra Ponte, Université de Montréal, Montréal (Canada); Nikos Skoutèlis, Technical University of Crete, Chania (Grecia); Gianni Talamini, City University of Hong Kong, Hong Kong (Cina); Guido Zuliani, The Cooper Union, New York (USA), Maria Gatto, Ufficio Relazioni Internazionali Università Iuav di Venezia, Clara Grano, Agenzia Erasmus+ INDIRE. \nI materiali digitali di Iuav Abroad sono disponibili su: http://www.iuav.it/Ateneo1/chi-siamo/Iuav-Acade/
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".