Enfermedad, contagio y salud en el campo.
Bibliographic record
Abstract
Un primer caso que podemos considerar para avanzar en la dirección anotada es el de uno autos judiciales contra un hacendado (el implicado se calificará como labrador) a quien se acusaba en octubre de 1802 (es decir, en tiempo de epidemia) de haber introducido y ocultado a un virolento. Como el origen de las informaciones es judicial, éstas resultan extremadamente reiterativas y el sistema de preguntas, y aún de respuestas, muy ritualizado. Aún así ofrece aspectos novedosos sobre la circulación en el campo de un enunciado como el de la salud pública. Por lo demás, tratándose de informaciones judiciales, tal vez valga la pena recordar que en ellas a nosotros no nos interesa la verdad sino la interpretación, ya que nuestro punto de vista no es el del juez, sino apenas el del historiador.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.114 | 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; 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".