Moldeo y fundición con arenas de las playas de Tenerife
Bibliographic record
Abstract
espanolEl presente proyecto trata de comprobar la capacidad de moldeo y fundicion de las arenas costeras de Tenerife. Las arenas han sido analizadas en cuanto a su composicion, granulometria, morfologia, etc., y estudiado su compor tamiento ante los aditivos aplicados en el moldeo: resina y catalizador. Para ello se ha hecho una cata de las arenas por todo el litoral de Tenerife conociendo el entorno y especificidades de la isla. EnglishThis project is designed to test the moulding and casting capacity of Tenerife’s coastal sands The sands have been analysed as to their composition, granulometr y, morphology, etc., including their behaviour when subjected to the additives applied during the moulding process: resin and catalyst. For this purpose, samples have been taken of the sands throughout Tenerife’s coastline knowing the island’s environment and particular features.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".