INTELLIGENTE SALZFABRIK SELF INTEGRATED PHARMACEUTICAL RAW MATERIALS INDUSTRY IN INDONESIA
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
ABSTRACT Currently, Indonesia's pharmaceutical industry is still heavily dependent on imported raw materials, almost 95% of the needed medicine raw materials (BBO) still have to be imported from abroad. Based on data from the Directorate General of Foreign Trade, Ministry of Trade Republic of Indonesia, it was showed that the pharmaceutical salt import in 2013 reached 3,152 tons and all of them needed to fulfill domestic needs. This study used literary study method by collecting data or information in accordance with the topic. Geographically Indonesia consists of islands large and small number of approximately 17,504 islands. Three quarters of its territory is the ocean (5.9 million km2), with a 95,161 km long coastline, the second longest in the world after Canada. This makes Indonesia the world's largest archipelago in the world. This written idea was created as a solution to the problem of dependence on medicine raw materials import in the pharmaceutical industry of Indonesia. The solutions presented are Intelligente Salzfabrik: The Concept of Self-Integrated Pharmaceutical Raw Materials Industry which is Energy Independence and High Accessibility on Coastal with Sea Toll and Power Flow to Achieve An Imported Medicine Raw Materials Independence in Indonesia. This development will be implemented in close proximity to coastal areas near the the sea so that it can simplify both cost and transportation required for the distribution of salt produced.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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