Bibliographic record
Abstract
It is with great honor; we present the proceeding of the 4th International Conference of Food Security and Sustainable Agriculture in The Tropics (IC-FSSAT) 2023, which was organized by the Faculty of Agriculture, Universitas Hasanuddin, and held online in the 15 – 16 February 2023. The proceeding of the previous conferences in this series has been published in the IOP conference series: Earth and Environmental Sciences (EES). The proceeding of the 4th IC-FSSAT consists of 225 reviewed papers across 10 main scopes; (i) Industrial-scale Agriculture, (ii) Food Agribusiness and Rural Development, (iii) Food Agribusiness and Rural Development, (iv) Biodiversity, Soil Health and Agricultural Practices (v) Integrated Pest and Disease Management, (vi) Plant Breeding and Biotechnology (vii) Agricultural Engineering, (viii) Digital Farming, (ix) Food Processing, Safety and Diversification and (x) Crop Production System. In addition to the excellent paper presentations at the conference, the conference also featured nine keynote and invited speakers with expertise in the field of the conference’s subjects. Please allow us to take this opportunity to thank the keynote speaker and the invited speakers: Dr. Tony Liwang (Oil Palm Plantation Fund Management Agency, Indonesia; Prof. Siti Kusujiarti (Warren Wilson College, USA); Prof. Bunyamin Tar’an (University of Saskatchewan, Canada); Prof. Sikstus Gusli (Hasanuddin University, Makassar- Indonesia); Dr. Thong Nguyen-Huy (The University of Southern Queensland, Australia); Dr. Didier Lesueur (Centre de cooperation Internationale en Recherche Agronomique pour le Developpement (CIRAD), France; Dr. Anwar Syed H. Rizvi Animal and Plant Health Inspection Service, USA; Prof. Hasil Sembiring (IRRI Indonesia); and Dr. Inamullah Khan (The University of Agriculture, Pakistan). I would like to express our deepest gratitude to all committees for this conference’s success and smooth running. Last but not least, a warm thank you to all academics, researchers, and observers of Faculties of Agriculture, Science, Animal Husbandry, and Forestry for their participation in submitting their article in the IOP proceedings series EES 2023. I sincerely look forward to all the contributions that will benefit and promote the development of a sustainable agricultural innovation sector toward achieving the SDGs and dealing with the triple planetary issues. Warm Regards, Muhammad JUNAID, SP., MP., PhD Conference Chairman Faculty of Agriculture, Hasanuddin University List of Conference 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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.478 | 0.373 |
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".