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
This chapter analyzes fuzzy reliability theory using bibliometric analysis. Different aspects of fuzzy have already been analyzed using bibliometric analysis, and a series of bibliometric tools have also been used. VOSviewer software was used to identify maps showing the most relevant trends. The analysis includes scientific articles, citations, journals, authors, universities, keywords, and countries. Results show that countries belonging mainly to Asia are at the avant-garde in terms of research in the field, China and India being the most productive countries in terms of the number of articles published, citations, and universities invested in the topic. Other countries in North America, such as Canada and the United States, and in Europe, the UK, Poland, Italy, and France, also show a great interest in this area of science. Research on the topic is relatively recent. The first articles were published in 1991; therefore, it presents excellent opportunities that will quite possibly attract researchers and universities from different regions of the world.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it