VISUALISASI DATA INTERAKTIF DATA TERBUKA PEMERINTAH PROVINSI DKI JAKARTA: TOPIK EKONOMI DAN KEUANGAN DAERAH
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
Based on statistics from data.id, in the first quarter of 2016, there are 1,137 datasets distributed at 32 institutions and 18 groups in Indonesia. DKI Jakarta Province contributes to these data at the most, i.e. 714 datasets. A lot of accessible open datasets have an impact on the availability of valuable information that can be extracted to good use, for businesses, governments, and personal lives. To get the desired information, an exploratory data analysis is needed to make data more alive. The goal of this research is to provide a proper visualization of the given data. Data visualization is a way (perhaps a solution) to communicate abstract data, to aid in data understanding by leveraging human visual system. The result of this visualization is effective and engaging charts appropriates to the given data and can be run on mobile platforms.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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