Bibliographic record
Abstract
Biomath is an established conference series providing meeting forums for scientists from different disciplines and from different countries and continents, who develop and apply mathematical and computational tools to study phenomena in the broad fields of life sciences. It follows a tradition of scientific meetings on Biomathematics held at the Bulgarian Academy of Sciences since the 1990s. The traditional support from the academic units of the Bulgarian Academy of Sciences and the Bulgarian Universities has been getting stronger with time. Further, we need to acknowledge the substantial contribution of University of Pretoria in South Africa to the success of this conferences. In fact, one of the main driving forces for the conferences since 2011 is the collaboration between the Institute of Mathematics and Informatics at the Bulgarian Academy of Sciences and the Department of Mathematics and Applied Mathematics at the University of Pretoria. The contribution of University of Pretoria and the personal contribution of Prof Jean Lubuma were acknowledged in 2012 by awarding to Prof Lubuma the Sign of Honour of the Bulgarian Academy of Sciences, the Academy's highest recognition to international scolars. As part of this collaboration, University of Pretoria hosted in 2015 a satellite conference to Biomath 2015. In this context it is quite natural to have in 2017 the conference Biomath taking place in South Africa with University of Pretoria as a host. Biomath 2017 is indeed international as it attracted participants from 20 countries: Belgium, Botswana, Bulgaria, Cameroon, Canada, Chile, France, Germany, Indonesia, Kenya, Nigeria, Poland, Portugal, Senegal, South Africa, Spain, Turkey, USA, Uzbekistan, Zimbabwe. Biomath conferences have a strong emphasis on supporting and promoting young scientists. The 2017 Biomath School for Young Scientists has over 30 participants.The support to young researchers provided by the Society of Mathematical Biology, the South African National Research Foundation, the Center of Excellence in Mathematical and Statistical Sciences at the University of Witwatersrand, the DST/NRF SARChI Chair on Mathematical Models and Methods in Biosciences and Bioengineering and the Department of Mathematics and Applied Mathematics at University of Pretoria is acknowledged. Biomath pays special attention to the publication of the presented scientific communications. Original papers based on the presentations in Biomath 2017 are invited for submission to the special issue Biomathematics of the journal Mathematical Methods in the Applied Sciences and in the journal BIOMATH. Further, BIOMATH will publish full refereed proceedings in Issue 2 of Volume 6. We request the support of all participants for high quality publications. International and interdisciplinary conference like Biomath 2017 is only possible through the efforts of many. We are grateful to International Steering Committee, to the Organizing Committee, to the Keynote and Invited Speakers, to all participants. We wish to all productive time at the conference. We hope that Biomath 2017 will have a stimulating effect on your research and future career.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.619 | 0.679 |
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".