Bibliographic record
Abstract
Modelos de un mismo sistema pueden diferir mucho en su escala, nivel de detalle, o mas precisamente en el caso de modelos dinamicos, en la dimensionalidad del espacio de estados. Se analizan las implicaciones de esta dimensionalidad, tanto en general como mas especificamente en relacion a modelos de crecimiento. Se comenta sobre la naturaleza de la modelizacion, se distingue entre modelos descriptivos y predictivos, y se explican brevemente los conceptos de sistema dinamico y espacio de estados. A traves de ejemplos, se demuestran limites a la previsibilidad que pueden hacer imposible las predicciones confiables a nivel individual. El entender perfectamente el funcionamiento de un sistema, o el simularlo en ordenador, no implica el poder predecir su comportamiento. Aunque los modelos detallados son utiles para fines de investigacion, modelos agregados de baja dimensionalidad son generalmente mas apropiados para la gestion.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".