APLICAN TÉCNICAS NUCLEARES PARA ANALIZAR LA CERÁMICA ZAPOTECA
Bibliographic record
Abstract
EL INSTITUTO DE INVESTIGACIONES ANTROPOLOGICAS, EN COLABORACION CON OTRAS INSTITUCIONES DE EDUCACION DEL PAIS, UNIVERSIDAD DE LAS AMERICAS, DE PUEBLA; ESTADOS UNIDOS, PENNSYLVANIA STATE UNIVERSITY Y CANAD , ROYAL MUSEUM, APLICA NOVEDOSAS TECNICAS NUCLEARES (PIXE), DIFRACCION DE RAYOS X, TERMOLUMINISCENCIA Y AN LISIS ARQUEOLOGICOS, PARA DETERMINAR LA PROCEDENCIA PREHISP NICA LOCALIZADA EN LA SIERRA DE JU REZ, EN OAXACA. EN ESTE PROYECTO, EN EL CUAL SE TRABAJA PARA DETERMINAR LA AUTENTICIDAD DE COLECCIONES DE URNAS ZAPOTECAS, PARTICIPAN, ADEM S DE LOS INVESTIGADORES DE ESTA CASA DE ESTUDIOS DEL INSTITUTO DE FISICA, ASI COMO DE LAS FACULTADES DE FILOSOFIA Y LETRAS, QUIMICA Y DE CIENCIAS, ESPECIALISTAS DE LOS MUSEOS REAL DE ONTARIO Y GADINER, DE CANAD . LUZ LAZOS RAMIREZ, DE ANTROPOLOGICAS, EXPLICO QUE LAS METODOLOGIAS QUE SE APLICAN EN ESTA INVESTIGACION, EN PARTICULAR LOS PROCEDIMIENTOS NUCLEARES, MEDIANTE EL ACELERADOR DE PARTICULAS PELLETRON DEL INSTITUTO DE FISICA, NO SOLO SE EMPLEAN PARA EL AN LISIS DE CER MICA PREHISP NICA, SINO TAMBIEN EN HUESOS, METAL, PINTURA DE CABALLETE Y PAPEL. DESTACO QUE EL ACELERADOR DE PARTICULAS PELLETRON, INSTRUMENTO QUE SOLO EXISTE EN LA UNAM, PERMITE LA REDUCCION DE MUESTRAS NECESARIAS PARA ESTE ESTUDIO, ADEM S DE BAJAR LOS COSTOS DEL PROCEDIMIENTO. ESTA TECNICA ES BASTANTE ACCESIBLE Y BRINDA CALIDAD Y RAPIDEZ EN LA INFORMACION, ASPECTOS QUE LA CONVIERTEN EN UNA TECNICA IDONEA PARA ESTE TIPO DE AN LISIS, SOBRE TODO CUANDO SE HABLA DE PIEZAS CON VALOR ARTISTICO.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".