Tumores intracraneanos del niño
Bibliographic record
Abstract
Introduccion. Los tumores intracraneanos (TIC) pediatricos son las neoplasias solidas mas frecuentes en ninos. Se presenta la experiencia del Hospital Infantil de Mexico Federico Gomez (HIMFG) de los ultimos 36 anos. Material y metodos. Se utilizaron los siguientes archivos del HIMFG: Clinico, de los Departamentos de Neurocirugia y de Patologia. Los resultados se compararon con los datos del Hospital for Sick Children de Toronto y del Instituto Nacional de Pediatria de Mexico, D. F. Resultados. En el HIMFG, 55% de los pacientes eran del sexo masculino. Predominaron desde lactantes mayores hasta escolares, con mas de 50%. Los tumores fueron: 397 supratentoriales y 413 infratentoriales. Los mas frecuentes fueron: astrocitomas (32%), meduloblastomas (19%), craneofaringiomas (11%) y ependimomas (10%); en el quinto lugar quedaron los germinomas (4%). Los gliomas mixtos, los meningiomas, los tumores neuroectodermicos primitivos y los ependimoblastomas representaron de 1 a 3%. Conclusiones. En el HIMFG, los 4 tipos mas frecuentes de tumor fueron: astrocitomas, meduloblastomas, craneofaringiomas y ependimomas. El trabajo de campo del HIMFG ha tenido un desarrollo exponencial desde la mitad de los anos setenta. Actualmente, el volumen de pacientes manejado por el HIMFG es semejante a, o rebasa discretamente, al de otras instituciones.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".