Bibliographic record
Abstract
The purpose of this paper is to briefly evaluate and to give some information about the 15th International Society of Scientometrics and Informetrics (ISSI 2015), which was held in Boğaziçi University on June 29 - July 4, 2015. ISSI 2015 hosted more than 300 participants and it is pleasing that large number of audiences have shown interest in the Conference. 54% of the full papers and research in progress papers and 66% of the posters and ignite talks were accepted to be presented in the Conference. When the countries of the researchers that were contributed to the Conference were examined, it was realized that people from Republic of China, The United States of America, Canada, Spain and The Netherlands were in the top of the list in terms of the number of contributions. Selected papers will be published in Scientometrics which is an ISSI 2015 special issue. The next International Society of Scientometrics and Informetrics Conference will be held in Wuhan, People’s Republic of China, in 2017.
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 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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".