Medio ambiente
Bibliographic record
Abstract
Destacamos en esta entrega la Sentencia del TJUE de 12 de junio de 2025, en la que se vuelve sobre una cuestión que ha aparecido varias veces en los últimos años: el estado de conservación de la especie canis lupus (lobo). En este caso la sentencia comentada tiene el atractivo singular de tratar de las peculiaridades de la situación cuando la especie debe considerarse en Estados vecinos. Igualmente vuelven a ser objeto de tratamiento jurisprudencial los caudales ecológicos establecidos en el Plan Hidrológico de la cuenca del Tajo. En esta ocasión la STS de 17 de julio de 2025 presenta la peculiaridad de que el recurrente pretende que los caudales establecidos para la tercera fase, lo sean desde la primera, pretensión que desestima el TS. Finalmente se destaca la STS de 3 de julio de 2025 que establece la consideración del Plan Director de la Red de Parques Nacionales como directriz básica a tener en cuenta (singularmente los criterios de zonificación) a la hora de la redacción de los Planes de Ordenación de los Recursos Naturales de las CCAA, aunque se refieran a espacios que no tengan la consideración de Parques Nacionales.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.153 | 0.052 |
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".