Bibliographic record
Abstract
The problem of the stage barrier has interested performers, educators and scientists since time immemorial and remains extremely relevant for many active personalities as politicians, presenters, especially athletes and performers to this day. Sometimes even a self-confident person panics in front of a large audience. However, if fear, as a feeling that helps in difficult life situations, is quite normal, then phobia is a very intense emotion that forces you to change your life plans, hinders the realization of dreams.In the situation of stage performance, we are dealing with glossophobia, which in the medical dictionary is marked asa total fear of performing on stage. For most people, the excitement in front of the stage is based on the fear of losing their professional "face", to appear in front of the audience in the unattractive light of a low-intellectual person. Stage activity for a pianist-performer will always be an exciting phenomenon, but there are performers with a strong psyche who will turn any excitement to their advantage, accumulate all their performing abilities.S. Naumenko, G. Tsypin, G. Kogan, L. Barenboim, A. Rubinstein, O. Goldenweiser, S. Savshinsky, A. Sannikov paid special attention to the problem of stage excitement. The article also reveals the vision of solving the problem of stage excitement by the famous English teacher E. Weiss. Key words: performer, performer's consciousness, repertoire, concert state, emotional state, stage barrie.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.028 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.007 |
| 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".