International Conference on Innovative Technology and Sciences (ICITSS)
Bibliographic record
Abstract
Abstract “The 21st Century Technology and Sciences: Challenges, Obstacles, and Opportunities in the New Norms Era” 12 - 13 November 2020 PREFACE The International Conference on Innovative Technology and Sciences (ICITSS) is annual conference of University College of Yayasan Pahang Malaysia. This conference was initiated by Manager of Research Management Centre, University College of Yayasan Pahang “Mr. Dedi Sanjaya” The theme for the ICITS 2020 is The 21 Century Technology and Sciences: Challenges, Obstacles, and Opportunities in the New Norms Era”. As the COVID-19 pandemic continues, many sectors have been affected and faced a lot of challenges and uncertainties. We hope that this conference will provide an excellent platform and ample opportunity to share research ideas related to the current issues during the pandemic. These insightful research results, hopefully, will be able to provide comprehensive, adaptive, creative, and innovative solutions to deal with the issues. Furthermore, the participants will have the privilege to gather and exchange knowledge and establish networking across various disciplines in a single platform. In this virtual conference, we are honored to have 3 distinguished keynote speakers and 5 invited speakers from 6 countries, namely Tan Sri Dato’ Sri Dr. Dzulkifly Abdul Razak from Malaysia, Prof. Amrin Saragih from Indonesia, Prof. Dr. Nena P. Valdez from the Philippines, Assoc. Prof. John Adamson from Japan, Dr. Robbie Lee Sabnan from Singapore, Asst. Prof. Dr. Azhar Jaafar from Malaysia, Asst. Prof. Dr. Tan Li Pin from Malaysia and Dr. Poonsiri Thinapt from Thailand. We are also delighted to receive approximately 335 participants from various countries such as Malaysia, Indonesia, Thailand, India, Canada, Saudi Arabia, Egypt, Brunei, Philippines, Japan, Singapore, and many more. On behalf of the organizing committee, I would like to take this opportunity to express my sincere appreciation to Universiti Teknologi Brunei, Universitas Sumatera Utara, Universitas Negeri Medan, Universitas Bengkulu, Universitas Teuku Umar, Phetchaburi Rajabhat University and Universiti Sultan Zainal Abidin for the collaboration in organizing this conference. Our sincere thanks should also be conveyed to all the keynote speakers and invited speakers for their willingness to present their knowledge and ideas at the conference. Besides that, I would like to take this opportunity to express my heartfelt appreciation to the committed and passionate committee members. The ICITSS 2020 Organizing Committee hopes you will enjoy reading this JPCS volume. List of Patron, Steering Committee, Organizing Committee are available in this pdf.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.212 | 0.137 |
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".