KTH Industrial Engineering and Management NONLINEAR ISOVISCOUS BEHAVIOUR OF COMPLIANT JOURNAL BEARINGS
Bibliographic record
Abstract
God. I give my deepest gratitude to my wife, Woori. She has given me a big support and love. And she waited patiently for me to complete my thesis and taking care of our two lovely children. I would also like to thank my daughter, Ye-Eun for growing up healthy and bringing joy to my family. I would like to welcome my newly born son, Ye-Lang, to my family. I want to thank both of my parents and families in Korea and Canada for their care, love and support. I would like to thank my supervisor, Professor Sergei Glavatskih for giving me an opportunity to study and research under his guidance. He has brought me into the field of fluid film bearings and there are many things to learn and absorb from his expertise. His valuable discussion, support and help are gratefully acknowledged. Without his supervision and friendship, this work was not possible to accomplish. I would also like to thank my colleagues from Luleå University of Technology
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 | 0.000 | 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 | 0.000 | 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".