Pembuatan Video Profil Perpustakaan di Dinas Kearsipan dan perpustakaan Provinsi Sumatera Barat
Bibliographic record
Abstract
AbstractThe kind of research this is qualitative with the methods descriptive. Data was gathered through observation and conducting interviews with outstanding librarians and pemustaka for the local office of chancery and libraries the province of west sumatra .As well as by assistance material the manner it should be has to do with video. Writing in the papers were intended to discuss steps that video production profile of the library and libraries in the chancery. west sumatra provinceThis study seeks to describe the stages of making a video of the profile of the library and libraries in the chancery west sumatra province. Based on an analysis data can be concluded that stages in making video library profile as follows: first, production in pre the done before the video consisting of invention an idea or ideas, sinopsis, treatment, storyboard, shooting the script, production production planning and preparation. Second, and hold what production developed at the praproduksi.Third, pascaproduksi end in the process of producing the video before video ready to served.Keyword: video, library
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.033 | 0.003 |
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".