Investigación sobre propiedades de nuevos fluidos industriales de bajo impacto ambiental como sustitutivos de gases fluorados para reducción del cambio climático
Bibliographic record
Abstract
A lo largo de los últimos 40 años, y a expensas de los Protocolos de Montreal (1987), Kyoto (1997), y más recientemente el Acuerdo de París (2015), se han ido desarrollando nuevas alternativas de fluidos medioambientalmente más limpios con respecto a los ampliamente utilizados fluorocarbonos (CFCs, HCFCs, HFCs, PFEs, etc), para su empleo en multitud de aplicaciones como son la refrigeración, limpieza de precisión, fluidos de transferencia de calor, entre otros. Los hidrofluoroéteres (HFEs) se presentan como una buena opción dadas sus propiedades termofísicas, y su bajo impacto sobre el medio ambiente. Esta Tesis ha basado su objetivo en la caracterización experimental de varias propiedades termofísicas (equilibrios líquido-vapor, densidad a alta presión, viscosidad a alta presión, velocidad del sonido a alta presión, y capacidades caloríficas), de cuatro hidrofluoroéteres de alto peso molecular, y de sus mezclas binarias con alcoholes o éteres. Para las propiedades obtenidas se han aplicado correlaciones a distintas ecuaciones, así como modelos matemáticos.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".