Detecting the location of pain by transferring its sensation from a person to a another one by EM waves in BBI technology
Bibliographic record
Abstract
Patients in a coma are unable to express their problems, including pain. Therefore, it is necessary to examine their feelings, including pain and its location, in a reliable manner. This research presents a novel method for transmitting feelings and pain between two individuals through the exchange of waves. The method involves designing an antenna that captures the patient's blood waves, amplifies them, and transmits them to the blood of a healthy person. This antenna is composed of materials such as copper, iron, magnetic generators, ionized liquids, and blood from animals like rabbits. Blood molecules, such as hemoglobin, which contain oxygen and iron, exchange information with cells and sensory stimuli, such as neurons, by receiving and emitting spin waves. These waves are then transmitted to biological antennas and the blood of the second person. Consequently, the healthy individual can perceive the patient's pain and determine its location. Prior to the transfer process, the voltage at various points on the bodies of both the patient and the healthy person is analyzed and simulated using computer models.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".