Pembuatan Purwarupa Songket Pakaian Adat Silungkang di Kecamatan Silungkang Kota Sawahlunto Sumatera Barat (Studi Kasus: Pada Kerapatan Adat Nagari Silungkang Dan Kantor Disperindag Kota Sawahlunto)
Bibliographic record
Abstract
AbstractThe process of making a Silungkang Songket prototype in Sawahlunto City uses a descriptive method with data collection techniques through interviews with traditional leaders and service offices. The process of making songket silungkang traditional clothing prototypes in Sawahlunto City is as follows: (1) data collection is done by interviewing techniques, (2) making a design in the form of a product to be made, (3) prototype making process in accordance with the work plan -the basic provisions of a topic that must be developed starting from making cover which is the hard skin on the outside of the book containing the title of the book, and accompanied by several supporting images; the preface contains a number of paragraphs which contain the thanksgiving of the author to Allah SWT and those who have helped and always support, a description of the prototype content, the basis and purpose of prototyping, the author's expectations, and the place, month and year when the preface was made ; the introduction contains a brief introduction to the Silungkang Songket and also a little about Sawahlunto City; the main contents of the book contain articles about silungkang songket which include history, motives and types based on the year.Keywords: silungkang songket, prototype
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.004 |
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".