МЕТОД ОЦІНКИ БІОМЕХАНІЧНИХ ВЛАСТИВОСТЙ ЕНДОПРОТЕЗІВ ТАЗОСТЕГНОВОГО СУГЛОБУ ПІД ДІЄЮ ФІЗІОЛОГІЧНИХ НАВАНТАЖЕНЬ
Bibliographic record
Abstract
Purpose. For a reasonable choice of optimal type of endoprosthesis requires evaluation in terms of not only clinical, but biomechanical parameters. The main task - to explore properties of the proximal bone areas with different types of feet EP on the basis of physiological stress and compare the results. Design/methodology/approach. Borrowing from the literature on professions and Pierre Bourdieu's theory of practice, starts from the assumption that editorials in practitioner-orientated publications are a form of cultural good traded on an internal symbolic market. By providing access to symbolic capital, trade in this good acts to bind together members of the accounting profession, yet trade in this good also has the potential to obscure a number of important, underlying social issues. The study is based on a close (textual) reading of editorials in the Canadian Chartered Accountant (subsequently renamed CA Magazine) from 1911 to 1999, and this reading is framed in the light of a number of macro-level and meso-level (contextual) changes. Findings. Conducted field experiments have shown preference trabecular-bionic endoprosthesis compared with the standard design in terms of stiffness and strength characteristics due endoprosthesis to bone tissue. Established described Spongy BT simulation method can be used in cases where there is a need to assess the quality of the bone implant connection and it is not possible by direct model experiment to recreate real regeneration BT. Originality/value. Our results are clinically important and can improve treatment.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.047 | 0.017 |
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".