Estudio de los flujos ocurridos en el 2007 en Chalala y Coquena, Purmamarca, provincia de Jujuy
Bibliographic record
Abstract
Investigation of the 2007 flows from Chalala and Coquena, Purmamarca, Jujuy Province. This work presents the results of the investigation of mudflows from Quebrada de Coquena of 7 March, 2007 and from Quebrada de Chalala of 29 March of the same year. These stream basins are tributary to the Quebrada de Purmamarca located in the Cordillera Oriental, Jujuy Province, Argentina. The studies focussed on the classification of the type of mass flow type and quantification of the magnitude of these events. Flow velocity was calculated using two different equations. Both methods produced similar results. Flow volu- me was measured directly in the field. The relationship between the total discharge (V) and the peak flow (Q p ) was estimated by using equations for similar flows from the geotechnical literature. Maximum erosional yield was estimated using the JICA method. The probability of large destructive mudflows inundating the fans of these streams is very high (>1/20) and their magnitude is class 5: a volume greater than 10 5 m 3 . The flow velocity, volume and frequency calculated in this study are va- luable for hazard mapping, the creation and placement of infrastructure, and land use planning.
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 | 0.000 | 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) | 0.000 | 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".