Wykorzystanie potencjału naukowo-badawczego i leczniczego oraz kondycja finansowa Narodowego Instytutu Onkologii im. Marii Skłodowskiej-Curie w latach 2017–2021
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose – The study concerns the National Institute of Oncology, which is the largest medical research institute in Poland. It presents the development of the institution and evaluates the scientific, research and treatment activities as well as the financial situation of the above‑mentioned institutions. Research method – The article is a case study. The method of examining documents and data contained in the annual activity reports of the Director of the NIO and its financial statements for the years 2017–2021 has been used. In evaluation the Institute, the indicators for public healthcare entities included in the regulation of the Minister of Health has been applied. Results – The National Institute of Oncology conducts extensive research and develops innovative treatment methods that are practically used in the diagnosis and treatment of cancer. He actively participates in a task of exceptional importance for improving public health in Poland, i.e. the National Oncology Strategy. The difficult financial situation of the entity is gradually improving. Originality/value/implications/recommendations – The issue of medical research institutes is not handled in the literature on public health or public finance. Therefore, this publication fills the existing gap to some extent and is part of the series of articles devoted to the above‑mentioned issues, implemented by the authors. entities.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.022 |
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 it