4th Global Conference on Materials Science and Engineering (CMSE 2015)
Bibliographic record
Abstract
IOP Conference Series: Materials Science and Engineering is publishing a volume of conference proceedings that contains a selection of papers presented at the 4th Global Conference on Materials Science and Engineering (CMSE 2015), which is an annual event that started in 2012. CMSE 2015, technically supported by the Institute of Applied Physics and Materials Engineering of University of Macau, organized by Wuhan Advance Materials Society, was successfully held at the University of Macau-new campus located on Hengqin Island from August 3rd-6th, 2015. It aims to bring together leading academic scientists, researchers and scholars to exchange and share their experience and research results on all aspects of Materials Science and Engineering, and to discuss the practical challenges encountered and the solutions adopted. Macau, one of the two special administrative regions of the People's Republic of China, where East meets West, turned out to be an ideal meeting place for domestic and overseas participants of this annual international conference. The conference program included keynote presentations, special sessions, oral and poster contributions. From several hundred submissions, 52 of the most promising and mainstream, IOP-relevant, contributions were included in this volume. The submissions present original ideas or results of general significance, supported by clear reasoning, compelling evidence and methods, theories and practices relevant to the research. The authors state clearly the problems and the significance of their research to theory and practice. Being a successful conference, this event gathered more than 200 qualified and high-level researchers and experts from over 40 countries, including 10 keynote speakers from 6 countries, which created a good platform for worldwide researchers and engineers to enjoy the academic communication. Taking advantage of this opportunity, we would like to thank all participants of this conference, and particularly the authors of all accepted papers for their high quality and fruitful contributions. Special thanks are due to all reviewers for their careful critical reading of the manuscripts and useful comments and suggestions. We do hope that this volume will be beneficial for readers to their future research endeavours and careers. We also gratefully acknowledge tremendous efforts and dedication of many individuals, especially CMSE Conference Secretary Ms. Liu Qin, Editor Anete Ashton and all the Editorial Board members in IOP Publishing for their support in producing the proceedings of this event. Guest Editors: Prof. Harry E. Ruda University of Toronto, Canada Dr. Alexander Khotsianovsky Pisarenko Institute of Problems of Strength of the National Academy of Sciences of Ukraine, Ukraine
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| 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".