Bibliographic record
Abstract
The 5th International Conference on Mechanical, Automotive and Aerospace Engineering (ICMAAE) was initially scheduled to take place as a face-to-face conference in 11-13 August 2020 in Kuala Lumpur, Malaysia. However, due to the covid19 pandemic, the conference was finally conducted virtually a year later in 22 – 23 June 2021. Nevertheless, the conference has attracted fellow researchers, academicians, and industry professionals from 13 countries, including Bahrain, Bangladesh, Canada, India, Indonesia, Malaysia, Morocco, Nigeria, Pakistan, Saudi Arabia, Tunisia, UAE, UK and USA, to share their experiences and ideas while renewing old friendships and making new acquaintances. The topics of the conference cover a wide range of fields in mechanical, automotive, and aerospace engineering. The conference received 134 papers where 96 papers were accepted for presentation. Among these papers, 25 papers are selected for publication in IOP Conference Series: Materials Science and Engineering. The other papers are submitted for publication in four indexed journals including CFD Letters, FME Transactions, IIUM Engineering Journal and Journal of Advanced Research in Fluid Mechanics and Thermal Sciences. The success of ICMAAE 2021 depends completely on the effort, talent, and energy of researchers in the field of Mechanical, Automotive and Aerospace engineering who have submitted papers on a variety of topics. We are indeed glad at the favourable response received from the scientific community around the world. List of ICMAAE 2021 Conference Organizing Committee is available in this pdf.
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 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.515 | 0.389 |
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".