El cerebro y el arte. Evidencia de las pinturas rupestres del sur de Europa
Bibliographic record
Abstract
Se ha definido al ser humano, en un afán de mostrar su carácter pretendidamente excepcional, como el mono parlante, el bípedo implume, el animal que ríe, el animal que fabrica y utiliza instrumentos (homo faber), el animal que sabe (homo sapiens), el ser que se encuentra a medio camino entre la bestia y el ángel (Pascal), el mono sin pelo (Desmond Morris), el mono tecnológico, pero nunca se ha intentado definir al hombre como el homo musicalis, el animal que hace y escucha música o como el homo artisticus, el animal que hace arte. “¿Qué clase de mono somos?” se pregunta Raúl Gutiérrez Lombardo en su libro (Gutiérrez Lombardo, Martínez-Contreras, & Vera Cortés, 2014). Una respuesta parcial a esta pregunta es: el hombre es el mono que inventó el arte.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".