Bibliographic record
Abstract
Ingin belajar ke luar negeri tanpa biaya? Kalau Anda adalah karyawan yang ingin kuliah lagi, pelajar yang sedang mencari sekolah, atau orang tua yang ingin menyekolahkan anak sampai luar negeri, temukan caranya di buku penting ini. Ahmad Fuadi telah berhasil mendapatkan 10 beasiswa, fellowship, exchange program, dan residency dari Amerika Serikat, Inggris, Kanada, Singapura sampai Italia. Apa saja itu? - The Fulbright Scholarship, The George Washington University, Amerika Serikat, 1999-2001 - The British Chevening Award, University of London, UK, 2004-2005 - The Ford Foundation Award 1999-2000 - Columbian School of Arts and Sciences Award, The George Washington University, 2000-2001 - CASE Media Fellowship, University of Maryland, College Park, 2002 - Indonesian Cultural Foundation Inc. Award, 2000-2001 - SIF-ASEAN Visiting Student Fellowship, National University of Singapore, 1997 - Youth Exchange Program, Indonesia-Canada, 1995 - Bellagio Art Residency Program, Bellagio Center, Lake Como, Italy, 2012 - Artist-in-Resident, University of California at Berkeley, Amerika Serikat, 2014 Simak 100 kiat berburu beasiswa luar negeri ala Fuadi di buku ini .
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.122 | 0.032 |
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".