PREFACE: The 2<sup>nd</sup> International Conference on Sustainable Cereals and Crops Production Systems in the Tropics (ICFST)
Bibliographic record
Abstract
The 2nd International Conference on Sustainable Cereals and Crops Production Systems in the Tropics (ICFST) was held on 23-24 September 2021 in Harper Hotel Makassar, Indonesia. The Conference was organized by Indonesian Agency for Agricultural Research and Development (IAARD)-Ministry of Agriculture of Indonesia, collaborated with International Maize and Wheat Improvement Center (CIMMYT) and Ministry of Research, Technology and Higher Education of Indonesia. The theme of the conference is “Strengthening Agricultural Resources Management to Support Food Security and Industry 4.0” with the sub themes of Breeding and Biotechnology, Crop Production Systems, Pest and Disease Management, Post Harvest, Socio-Economy and Community Development. The conference was conducted in two days offline/on site and virtual scientific sessions. Due to the pandemic reason, offline/on site meeting was limited to a maximum of 100 participants and the remaining 900 participants joined via virtual zoom meeting. The conference facilitate the research community focusing in food crops and provide platform for scientists to meet and interact with each other to share their knowledge and their research results along with the obstacles and challenges they faced in their development, achievement as well as experiences through the presentation of papers and discussion. This international conference is also an event to establish cooperation in the development of food crops research in the future as well as enhancing the knowledge of environmental protection with the current agricultural technologies. We would like to convey our deepest gratitude to the Minister of Agriculture of Indonesia, Keynote Speakers: Dr Kevin Pixley (Director of Genetic Resources Program CIMMYT & the CGIAR Research Program), Prof. Keerti S. Rathore (Texas A&M University, USA), Dr. Juan Landivar Bowles (Texas Agrilive-USA), Prof Bunyamin Tar’an (University of Saskatchewan Canada), Dr. Yu Shin Nai (Chung Sing University-Taiwan), Dr. Naori Miyazawa (Nagoya University), sponsors, organizing committee and also to all participants. We also would like to express our deepest gratitude to the Indonesian Agency for Agricultural Research and Development (IAARD) conducted such conference. We are looking forward to the 3rd ICFST that will be held on September 2023 in Bali Island. We expect that these future ICFST conference will be as stimulating as this most recent one was, as indicated by the contributions presented in this proceedings volume. Makassar, 23-24 September 2021 IAARD Indonesia List of Committees, conference photograph 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.199 | 0.122 |
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".