Bibliographic record
Abstract
Sono inseriti 4 poster tra i quali individuare quello che si sceglie di analizzare per la tesina scritta indispensabile per l'esame (cfr. le caratteristiche nel programma). \nLe didascalie descrittive sono le seguenti: \nPoster 1 (Ben Shahn, USA, 1967, manifesto contro gli esperimenti nucleari) \nPoster 2 (Frank Viva, P.E.N. Canada, 1996, Canada. P.E.N., un'associazione internazionale di scrittori inpegnata in campagne per la libertà di espressione, ha richiesto un poster per promuovere il fund-raising) \nPoster 3 (Loewy, British Red Cross, s.d., Regno Unito. Promozione di attività formative) \nPoster 4 (Studio Signo, Italia, 1991, manifesto per la mostra del Compasso d'Oro a Madrid, Istituto Italiano di Cultura) \n \nL'analisi va condotta facendo riferimento ai testi indicati in programma e alle lezioni del corso a cui - si ricorda - era fortemente auspicata la presenza come frequentanti (le diapositive utilizzate sono state inserite on line col titolo "materiali didattici")
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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; both teacher heads agree on what is shown here.
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".