Atlas Sur del Lago. Municipio Colón
Bibliographic record
Abstract
Hoy tenemos con nosotros un Atlas que compendia ese pasado e historia común, esas grandes potencialidades que Dios y la naturaleza nos otorgaron, desglosados en un lenguaje accesible y ameno y no menos profundo, que nos proporciona identidad y nos define como pueblo. Narraciones y gráficas, interpretaciones y mapas, poemáticas y leyendas, van construyendo el municipio Colón desde las más diversas perspectivas. Investigadores, cronistas, periodistas, personajes, artesanos, artistas, poetas y cantautores, fotógrafos, campesinos y amas de casa, han contribuido a la elaboración de esta obra, cuya investigación, observación y oficio, nos devela al municipio Colón por dentro, una mirada a esa Venezuela que se levanta cada día en el afán de construir su propia historia. Una mirada múltiple a esa Venezuela rural que puntualiza en el trabajo colectivo, los grandes retos del país. Uno de los 21 municipios del estado Zulia que contribuye a enriquecer nuestro país y que juntos en sus más diversas expresiones y particularidades conforman nuestra zulianidad.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.182 | 0.046 |
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".