Bibliographic record
Abstract
We made a turning trial of a twin-engine, twin-propeller, and twin-rudder ship “KAKUYO MARU”,\nthat has equipped the two sets of main engines and rudders, and a comparison was made between two\nengines and one engine as well as between two rudders and one rudder about the factors of turning. The\ntrial results are stated below.\n1) Comparing to the operation of two engines, the ratio of steady turning diameter (D/L), the speed\nreduction rate (RATE), and the time for turning (TIME) were large when the position of engine\nand the turning direction was the same. And, these decreased when rudder angle was large. Also,\nthe drift angle (ANGLE) was small and increased when rudder angle was large.\n2) In comparison with using two engines, D/L and TIME when using one engine and turning to the\nopposite direction of engine position were small and increased when rudder angle was large. Also,\nthe RATE and ANGLE were large and decreased when rudder angle was large.\n3) When using one engine, D/L and TIME of turning by one rudder were 1.1 to 1.6 times larger than\nthese of turning by two rudders at both turning directions and decreased when rudder angle was\nlarge. Also, RATE and ANGLE were as small as 0.7 to 1.0 times and increased when rudder angle\nwas large.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".