Epistemics for Learning Disabilities: Contributions from Magnetoencephalography, a Functional Neuroimaging Tool
Bibliographic record
Abstract
El síndrome Dificultades del Aprendizaje (DA) fue descrito en 1963 por S. Kirk. Desde entonces, diversas escuelas en EE.UU., Canadá y España han afinado su concepto y clasificación. La UCM en España ha propuesto una definición descriptiva y totalizadora, y ha estudiado empíricamente distin- tas manifestaciones, intentando descubrir sus marcadores biológicos y las características neurológicas de sus principales manifestaciones (dislexia, discalculia, disortografia, TDA, TDAH, etc.). Se describen los hallazgos en DA a partir de estudios como la magnetoencefalografía (MEG), técnica ino- cua que recoge campos magnéticos generados naturalmente por el cerebro y analiza su distribución espacial para localizar los generadores neuronales responsables, proporcionando información simultánea sobre la estructura y la función cerebral en patrones de normalidad en el procesamiento cog- nitivo y patrones aberrantes propios de las particulares manifestaciones clínicas del síndrome DA
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".