Pelatihan Pemanfaatan Teknologi Drone dalam Pembuatan Video Promosi Wisata sebagai Optimalisasi Pengembangan Potensi Desa Wisata Kreatif Terong
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
Desa Wisata Kreatif Terong is beginning to be recognized by all parties as one of the pioneering tourism villages that "dares" in showing its identity, daring to introduce its local wisdom and daring to carry out new innovations to support the growth of Belitung Island tourism. However, the development of the village faces various challenges, including a lack of public understanding of tourism management and minimal access to relevant training. One of the needs for tourism village managers that must be present in tourism management is the creation of content to promote their tourism, so training is needed in the use of drone technology as an effort to optimize the development of tourism village potential packaged in the form of community service activities. This activity was attended by 20 participants consisting of members of the Tourism Awareness Group of Terong Village and Keciput Village, Sijuk District, Belitung Regency. This activity has produced several outputs, namely successfully increasing the knowledge and skills of the community in operating drones, creating a local creative team ready to play a role in creating promotional content on an ongoing basis, and strengthening the collaborative network between universities and the village government. For the sustainability of the program, it is recommended that similar training activities be carried out periodically with a wider scope of material, such as professional video editing techniques, digital marketing, and tourism social media management
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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