Bibliographic record
Abstract
Recuerdo perfectamente aquel día, 21 de septiembre de 2009, uno de los más difíciles hasta hoy. No sabía a quién echarle la culpa; si a Ecopetrol por brindarme la oportunidad de estar en Bogotá, a mis padres por no darme la orden de quedarme en la misma ciudad de ellos o a mi novio porque en gran parte sólo me fui para estar cerca de él Pensaba y pensaba recostada sobre la cama que muchos ya habrían usado. Tenía una baranda verde pastel con bordes que te lastimaban y dos colchones baratos, tan desgastados que los resortes salidos te chuzaban. La habitación medía 1.50 metros de largo por 90 centímetros de ancho; no tenía baldosas ni closet. El televisor estaba sobre el suelo y mis cosas en bolsas negras de basura. Mi refrigerador había quedado en el pasillo donde otros estudiantes sacaban la poca comida que lograba comprar, aunque ya hacía tres días que esos groseros no tenían nada para robarme porque se había terminado la comida y no tenía plata para comprar.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.108 | 0.031 |
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".