AKTIVITASORKES KRONCONG NADA KASIH DALAM MELESTARIKAN \nLAGU-LAGU KERONCONG DI DESA TRIHARJO KECAMATAN SLEMAN KABUPATEN SLEMAN DIY
Bibliographic record
Abstract
Aktivitas Orkes Keroncong Nadakasih memberi dampak positif bagi perkembangan \norkes keroncong dan lagu keroncong di Kabupaten Sleman Yogyakarta dalam upaya \nmelestarikan musik keroncong agar digemari oleh masyarakat dan generasi muda. \nMemberikan dampak positif bagi perkembangan musik keroncong melalui pertunjukan \nmusik, sarsehan serta aktivitas sosial lainnya, sehingga orkes keroncong Nadakasih tetap \nberkiprah sebagai orkes keroncong yang memiliki potensi pemain yang cukup baik saat ini. \nPelayanan publik secara kronologis mengalami peningkatan dalam membangun bangsa \ndengan tetap konsisten menyebarkan repertoar musik keroncong sebagai penguatan jati diri \nbangsa. \n \nKata Kunci: Aktivitas, Orkes Keroncong Nadaksih,Melestarikan Lagu Keroncong
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.006 |
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".