Building Interest in Agricultural Research Through User Education Activities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Agriculture is a very important sector in supporting the development of Indonesia. One effort to improve agricultural success is through research and development. Various innovations of technology in agriculture as the result of research and development produced by the Indonesian Agency for Agricultural Research and Development. Agricultural information generated needs to be introduced to the younger generation. For that, the Indonesian Centre for Agricultural Library and Technology Dissemination (ICALTD) sought to create collaborations with schools through user education for students. The materials were packaged in accordance with the level of student understanding in the form of audio-visual and printed materials. These activities are expected to provide an understanding of the importance of agriculture to the development of the nation as well as to foster a sense of interest in the world of research. This paper aims to provide an overview of collaboration between ICALTD and the school in library user education activities, particularly in the field of agriculture.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.007 |
| 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 it