Effect of Electromagnetic Field Radiation at 2300 MHz on Wistar Rats
Bibliographic record
Abstract
Introduction: In the past decades, mobile phones have been increasing the amount of non-ionizing radiations in the form of high electromagnetic field radiations (EMFr) in all of our living surroundings and believed to cause tissue injuries in both animals and plants. Many studies now are exploring the consequences of cellular phone EMFr on physical and chemical changes in animals. Materials and Methods: We conducted experiments to study the biochemical consequences of 2300 MHz EMFr on wistar rats. Thirty six male albino adults were randomly divided into three sets and each set divided into test and control groups (Each group n=6, total six groups). The set I, II and III groups with controls were exposed to 2300 MHz irradiation for one hour per day according to their body weights for 30, 50 and 70 days, respectively. Blood serum was collected for all the groups to monitor for protein diminution and alkaline phosphatase (ALP) activity. Results: Our data revealed that exposure to the irradiation caused significant ALP levels, which increased at >50 and >70 days. The exposed animals showed modest changes in the protein and ALP levels as well as reduced body weights. There were significant deviations observed in physiological parameters of the exposed animals such as food and water intake and body temperature when compared to the controls. Conclusions: This study raised the possibility that constant usage of mobile phones likely to cause other abnormal tissue related problems.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".