[no title]
Bibliographic record
Abstract
Water a very important basic human need. Currently, water has even become an economic commodity. Based on the results of the annual recapitulation of the RIAU Provincial Report For Rokan Hulu Regency, there are 103 Drinking water Depots and data obtained are 49 Depots Feasible and 59 Depots Unfit for Food Sanitation Hygiene. From the initial data survey, new information was obtained from 7 depots that carried out laboratory examinations from the existing 15 depots. This study aims to evaluate the operations of the Refillable Drinking Water Depot in the Rambah Health Center in 2020. The method used descriptive qualitative research which was conducted in June in the working area of the Rambah Health Center, Rokan Hulu Regency, RIAU Province. With research subjects 5 Refillable Drinking Water Depot, sanitarian officers, Head of Health, Workers and consumers. From the results of interviews and observations, it was found that the knowledge, hygienic sanitation of Refillable Drinking Water Depot owners was inadequate and only some had a Business License the implementation of standard water testing laboratory tests once 6 months is not in accordance with the applicable regulations, namely once 3 months (Permenkes 2002), the source of raw water used 2 Refillable Drinking Water Depot regular wells 3 Refillable Drinking Water Depot wells BOR, Supervision from Sanitarian puskesmas has not been running regularly and optimally due to limited budget and during the Covid pandemic 19.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.062 | 0.012 |
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".