Bibliographic record
Abstract
A.PendahuluanBismillahirahmanirahim...Puji syukur kita panjatkan kehadirat Allah SWT karena berkat rahmat dan hidayahnya sehingga kita di beri kesehatan dan kesempatan untuk bisa menyelesaikan laporan evaluasi akhir Mahasiswa Kuliah Kerja Lapang Plus (KKLP) STISIP Muhammadiyah Rappang Tahun 2015 Desa Tonrong RijangDan tak lupa kita haturkan shalawat dan taslim kepada junjungan Nabi Muhammad SAW, Nabi yang memperjuangkan agama islam selama 23 tahun lamanya di Mekkah dan MadinahDalam penyusunan laporan evaluasi akhir ini kami mengacu pada buku panduan profil desa, observasi serta hasil seminar perencanaan program kerja dan hasil seminar evaluasi bulanan sehingga laporan evaluasi akhir ini bisa selesai tepat pada waktunya
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.136 | 0.033 |
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".