Agricultura y provisión de servicios ecosistémicos
Bibliographic record
Abstract
Imaginemos un campo, un establecimiento agropecuario, en producción en la región pampeana. Produce cultivos y carne vacuna. Anualmente vende sus cosechas de trigo, soja y maíz, y también vende ganado vacuno en pie. Compra maquinaria, fertilizante, herbicidas, pesticidas, vacunas. Repara instalaciones. Abona salarios. Tributa impuestos. Ahora imaginemos que las personas que viven y trabajaban allí retiran el ganado, se van, el campo deja de trabajarse. El flujo de salidas y entradas descripto en el párrafo anterior se detiene, pero ¿qué pasa en ese campo abandonado? Las áreas que habían sido cultivadas o pastoreadas se van poblando de vegetación espontánea en una sucesión de cambios. Algo parecido sucede con las poblaciones de insectos, microorganismos, pequeños mamíferos...
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 | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.104 | 0.036 |
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".