Bibliographic record
Abstract
Unlike most latter-day American sailing ships, the main-skysail-yard Red Cloud was not named after a significant stockholder or part owner. Instead, the namesake for this handsome ship was the famous Lakota war chief who had been one of the most formidable opponents of the U.S. Army on the American plains. The ship bore a carved figurehead representing the warrior chieftain, which lamentably cannot be seen in this photograph. \nRed Cloud began seafaring in the California wheat trade. This photograph, taken in San Francisco, shows the ship apparently drying sails after a fog or early rain. The skysail yard on the main has either been sent down or permanently removed for Red Cloud originally had one. Of interest is the long spanker boom and hoisted gaff. The small gaff at the main is also reminiscent of an earlier style of rigging. Particularly noteworthy was the long poop on Red Cloud—108 feet stretching nearly to the mainmast and almost half the length of the deck. While there were down easters with long quarterdecks, such long poops were more characteristic of earlier packet ships. The poop rail is easily seen marching into the main chains. Red Cloud also manifests an elliptic stern which is also unusual in American wooden sail of this period. Earlier clipper ships used this type of stern and Canadian and English wooden ships almost always used this form; the latter-day large wooden ship typically had a semi-elliptical stern with a handsome transom—frequently carved. Both are attractive and a coin would have to be tossed to determine the advantages of one over the other. Some have reported that the semi-elliptical stern was easier to construct. Perhaps. The reef points in the upper topsail on the mizzen are intriguing, as are the normally absent reef points in the much deeper topgallant sail. Not too many years after Red Cloud struck the waves, riggers routinely divided topgallants for easier management and smaller crews. One can only imagine how deep the main topgallant would be with its yard hoisted. A few years earlier, the topsails of a large full-rigged ship were doubtless of equivalent area to the topgallants of a big 2,000 tonner like Red Cloud. \nRed Cloud only sailed under the stars and stripes for 5 years. In 1882, a German firm bought Red Cloud and renamed the ship Carl Friedrich. Carl Friedrich stranded in 1893.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.590 | 0.380 |
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".