Bibliographic record
Abstract
This essay tries to find a way to reduce the noise of home made Suzuki gear boxes by analyzing the relationship between gear box noise and gear precision items. Three sample assemblies made at home and in Japan are chosen and comparative testing and checking on gear box noise and gear parts precision are carried out. Comparative analyses of some illustrations show that, on the basis of results from measuring and testing the relationship between gear components and the noise of national or Japanese gearshifts used in Suzuki automobiles, parts that reach the design demands don't mean that the gear box is definite to be up to the noise standard. The item affecting gear accuracy, which contributes a lot to the noise of gear box, is a radial tooth to tooth composite error. results from the relative analysis of three grade and four grade value of gearshift noise and the average value of error in corresponding gear pair, by utilizing the relative coefficient of “CORREL” . Based upon close study of the manufacturing process and workmanship of gears, proposals are put forward for reducing noise, in the hope of establishing technical grounds for the reduction of the noise of home made Suzuki gears.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".