Survey Identifikasi Pulau-pulau Tenggelam di Teluk Jakarta
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Jakarta adalah kota pesisir yang memiliki area berbentuk pulau di wilayah Utara tepatnya di Kabupaten Kepulauan Seribu. Pulau-pulau ini merupakan aset daerah yang harus dijaga keberadaannya. Pulau dapat berfungsi sebagai sumberdaya ekologis yang memberikan jasa lingkungan kepada wilayah sekitarnya. Penelitian ini akan mencoba mengidentifikasi pulau-pulau yang tenggelam yang ada di dalam area Teluk Jakarta. Tujuannya adalah memberikan informasi kepada khalayak umum tentang kondisi terkini pulau yang tenggelam, kemudian memberikan rekomendasi kepada pihak terkait untuk melakukan upaya restorasi pulau-pulau tersebut. Hal ini penting dilakukan agar pulau-pulau tersebut tidak hilang dari catatan sejarah dunia.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.066 |
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 it