The influence of targeted treatment on stereognosis and somatognosis in patients with chronic vertebrogenic algic syndrome
Bibliographic record
Abstract
This diploma thesis called "The impact of individual physiotherapy on stereognosis and somatognosis in patients with chronic back pain" contains basic knowledge about stereognostic and somatognostic function, it summarizes significant information about pain and the development of its chronic form, and last but not least it states possible causes of back pain disorders and its functional factors. One special part of the thesis describes non-standardized tests used to examine 21 probands who had been diagnosed chronic back pain and particularly it compares the results of these two examinations, the first of which was carried out before the beginning of physiotherapy and the second one carried out after 14 days of physiotherapeutic treatment. The aim of this thesis was to evaluate the impact of physiotherapy on stereognosis and somatognosis of patients with chronic back pain. All types of medical examination were tested without visual check. As a part of the medical examination a short form of McGill ́s questionnaire and a visual analogue scale indicating the intensity of pain were to be filled in by the probands to explicate their subjective feelings. The results of all but two tests improved after 14 days of physiotherapy, the therapy impact on function of stereognosis and somatognosis of patients with...
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".