Bibliographic record
Abstract
En este art?culo se examinan algunas obras de ficci?n argentinas ubicadas en Buenos Aires. Nuestro prop?sito es mostrar c?mo ciertas pr?cticas y percepciones sobre la vida urbana se encuentran mediatizadas por elementos de diversas tec nolog?as modernas. Partiendo, a manera de introducci?n, de un reciente tango de Mar?a Jos? Demare, Cibern?tica Buenos Aires,y de un cuento, Perra virtual, de Cristina Civaie, pasamos a considerar aspectos de novelas de Enrique Fogwill (Vivir afuera), Jos? Pablo Feinmann (Los cr?menes de Van Gogh), C?sar Aira (La villa), Ana Mar?a Shua (La muerte como efecto secundario) y Juan Martini (Puerto Apache). En nuestro comentario pretendemos se?alar algunos rasgos de una Buenos Aires cibern?tica, consecuencia de la presencia en ella de tecnolog?as asimiladas a la vida cotidiana y a la manera de ser de sus ciudadanos, que las usan hoy en d?a con toda naturalidad.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.181 | 0.063 |
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".