Bibliographic record
Abstract
When asking such a question, you see confusion in the doctor’s eyes. Experts from other fields of science will say that such a system does not allow any interference in its operation. So, what should we do, how should we be treated when joint pain, headaches and migraines appear, when arterial blood flow is disrupted in the area of the heart, feet and brain. Today, 96% of the population is diagnosed with deformities in the skeletal structures of the feet and spine, 90% of hyperactive children are not allowed to go to school without special pills. But no one thinks about the fact that all diseases are interconnected, and highly specialized doctors fight the body’s reactions, but not the causes. In all this, ignorance of the physiology of a self-regulating organism is seen. That all processes in the body are related to cell metabolism. Skeletal muscles are responsible for these processes, the pumping function of which is disrupted due to deformations in the musculoskeletal frame of the body and in their joints.
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 | 0.015 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.015 | 0.011 |
| Insufficient payload (model declined to judge) | 0.012 | 0.009 |
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".