Letter of thanks for <i>IJMSD</i>'s JCR debut in 2024
Bibliographic record
Abstract
Dear Readers, Authors, Reviewers, Editorial Board Members, Editorial Office Members, We are pleased and honored to inform you that, according to the 2024 Journal Citation Reports (JCR) from Clarivate released on June 20, 2024, the International Journal of Mechanical System Dynamics (IJMSD) received its first Journal Impact Factor of 3.4 (2023). IJMSD ranks 42nd out of 180 journals in the Engineering, Mechanical category (Q1, top 23.1%), and 39th out of 170 journals in the Mechanics category (Q1, top 22.6%). On behalf of the IJMSD Editorial Board, we would like to express our sincere gratitude to all authors, Editorial Board Members, peer reviewers, publisher Wiley, Editorial Office Members, and entire mechanical-engineering research community for their support and contributions to IJMSD. Since publishing the inaugural issue in November 2021, more than 2 years ago, IJMSD has received several other recognitions that include the following: it was selected for the High Starting Point New Journal Project of Excellence Action Plan for China Scientific, Technical, and Medical (STM) Journals in the founding year; indexed by Scopus in 2022, as well as by ESCI and Ei Compendex in 2023; selected in the first batch for the High Starting Point New Journal Project of Excellence Action Plan for STM Journals in Jiangsu Province in 2024; and included in JCR Q1 for both Engineering, Mechanical, and Mechanics categories. With the continued support from our research community, we hope that IJMSD will serve as a platform for the dissemination of new analytical and numerical results, for publishing high-quality and original research contributions, and for the promotion of the field of mechanical system dynamics.
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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 | 0.011 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.020 | 0.020 |
| Insufficient payload (model declined to judge) | 0.078 | 0.074 |
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".