Análisis comparativo y modelación de las situaciones de calidad del aire en una muestra de ciudades del mundo. Comparación con el caso de Medellín
Bibliographic record
Abstract
Para una muestra de 25 ciudades de diversos países del mundo, se recogió información sobre la calidad anual del aire para PM2.5, NO2 y ozono y sobre diversos parámetros de interés en cuanto a su relación potencial con la calidad del aire. Un análisis comparativo de dicha información y un modelo lineal que relaciona la calidad del aire con algunos de los parámetros es elaborado, con base en el nivel de aproximación que se logró entre las calidades reportadas y las predichas por la modelación. Los datos se basan en reportes e información disponible en páginas web y en reportes públicos e informes de investigación propios para los años 2012 y 2015. Se ha logrado plantear una perspectiva novedosa de la situación de la calidad del aire y del tipo de medidas estratégicas que se pudieran emprender para lograr mejorar la situación y llevarla a los límites deseables.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".