Análisis de oro en muestras geológicas:\n\nmétodo colorimétrico para ser utilizado en el campo
Bibliographic record
Abstract
"Se presenta un método para el análisis de oro en muestrasgeológicas, basado en una digestión con bromuro de potasio,ácido sulfúrico y peróxido de hidrógeno. El oro disuelto en formade AuBr4- es retenido en una esponja activada depoliuretano, y posteriormente es eluido con acetona. La concentraciónse determina espectrofotométricamente por la formaciónde un complejo con la tiocetona de Mitchler, cuya máximaabsorbancia es a los 550 nm. El método permite determinar oroen muestras geológicas, hasta una concentración en el orden de50 ppb. El uso de una columna de sílica gel, permite separar al complejo de oro de los pocos elementos interferentes. La precisióndel método es en promedio de un 10%, y la exactitud alrededorde 5-10%, medidas con muestras previamente analizadaspor los laboratorios ACME y ACTLABS de Canadá y con estándarescertificados del Canadian Certified Reference MaterialsProject (CCRMP). Las ventajas de este método son el cortotiempo requerido para el análisis, su bajo costo, y la posibilidadde ser instalado en el mismo sitio donde se realiza el trabajode prospección geoquímica o explotación del yacimientomineral."
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".