PATRIMONIO DE LA HUMANIDAD, EL GENOMA HUMANO
Bibliographic record
Abstract
AL OFRECER EN EL INSTITUTO DE INVESTIGACIONES BIOMEDICAS (IIBM) UNA CONFERENCIA SOBRE EL CONGRESO HUMAN GENOMA ORGANIZATION, EFECTUADO EN VANCOUVER, CANAD , ANTONIO VEL ZQUEZ ARELLANO, JEFE DE LA UNIDAD DE GENETICA DE LA NUTRICION DE DICHO INSTITUTO, EXPLICO QUE LOS ALREDEDOR DE 750 INVESTIGADORES ASISTENTES DE 40 PAISES A ESTA REUNION HICIERON UN PRONUNCIAMIENTO OFICIAL EN EL QUE SENALARON QUE, CON BASE EN LA DECLARACION DE LA UNESCO ACERCA DE QUE EL GENOMA HUMANO ES EL GRAN PATRIMONIO DE LA HUMANIDAD, LOS BENEFICIOS QUE SE OBTENGAN DE LAS INVESTIGACIONES GENOMICAS DEBEN COMPARTIRSE POR TODOS. EL ESPECIALISTA ACLARO QUE EN MEXICO EL TRABAJO M S IMPORTANTE AL RESPECTO SE REALIZA EN EL IIBM Y EST A CARGO DE MARIA TERESA TUSSIE Y LAURA RIVAS. DIJO TAMBIEN QUE LAS INVESTIGACIONES RELACIONADAS CON EL GENOMA HUMANO, QUE CONTIENE LA CONSTITUCION GENETICA COMPLETA DE CADA INDIVIDUO Y REPRESENTA LOS TRES MIL 500 MILLONES DE ANOS DE EVOLUCION DE NUESTRA ESPECIE EN LA TIERRA, HAN DADO UN NUEVO GIRO: EL RETO ACTUAL YA NO ES OBTENER LA SECUENCIA DE LOS PARES DE BASES QUE LO CONFORMAN, PUES ESTE PR CTICAMENTE YA SE CUMPLIO; AHORA ES DESARROLLAR METODOS PARA INTERPRETARLO.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".