Diagnosis Penyakit Hypertemia Menggunakan Metode Demster Shafer
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
Hyperthermia is a condition characterized by symptoms such as dehydration, muscle spasms, dizziness, weakness, nausea, vomiting, and fatigue, which can harm the patient's condition. The causes of hyperthermia can vary, ranging from lack of fluids to excessive physical activity. RSU Putri Bidadari has doctors who are experts in treating various diseases, including hyperthermia. However, several obstacles often occur in the direct consultation process, such as long queues, long distances, limited time, and costs. Therefore, a technology-based system is needed that is able to manage hyperthermia symptom data and help diagnose the disease early, so that patients can get information and early treatment quickly. This method is used to manage the symptoms selected by the patient to determine the possibility of the disease with a high level of confidence. Based on the analysis of the selected symptoms, this system is able to produce the most accurate diagnosis with the case of hyperthermia type Heat exhaustion, with a confidence level of 50.26%.
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 | 0.000 | 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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