Bibliographic record
Abstract
espanolEste articulo presenta un metodo geometrico que permite trazar una chalupa ballenera del siglo XVI, del tipo de la encontrada en Red Bay, Labrador, utilizando 2 plantillas y relaciones geometricas basadas en la relacion de la proporcion de la media y extrema razon, es decir, la relacion de la estrella de cinco puntas y triangulos asociados. Las dimensiones se eligieron para permitir la comparacion con la chalupa de Red Bay superponiendo los trazados. Este estudio no pretende que sea este es el metodo que se utilizo, pero quiere abrir una via de investigacion sobre metodos tradicionales no escritos que pudieron ser utilizados. euskaraArtikulu honetan metodo geometriko bat aurkezten da, Labradorreko Red Bayn aurkitutakoa bezalako XVI. mendeko balea txalupa bat marraztea ahalbidetzen duena, horretarako erabiliz 2 txantiloi eta urrezko ebakeraren proportzio erlazioan, hau da, bost puntako izarraren eta hari elkartutako triangeluen arteko erlazioan, oinarritutako erlazio geometrikoak. Neurriak aukeratu ziren Red Bayko txaluparekin alderatu ahal izateko trazatuak gainjarriz. Azterketak ez du iradokitzen erabilitako metodoa hori izan zenik, baina ikerketa ildo bat zabaldu nahi du erabili ahal izan ziren metodo tradizional ez idatzizkoez. EnglishThis article contains a geometric method for designing a whaling ship in the 16th century, of the type found in Red Bay, Labrador, using 2 templates and geometric ratios based on the extreme and mean proportion of reason, i.e. the five-point star ratio and associated triangles. The sizes have been chosen for the purposes of comparison with the Red Bay boat by superimposing the plans. The study does not seek to show that this was the method used, but seeks to open up an area for research on these ancient unwritten methods, which might have been used.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.013 | 0.002 |
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".