The 2010 Most Influential Bioelectromagnetics Journal Paper by Citation Award to Dr. Igor Belyaev, Dr. Catrin Baureus Koch, Dr. Olle Terenius, Dr. Katarina Roxstrom-Lindquist, Dr. Lars Malmgren, Dr. Wolfgang Sommer, Dr. Leif Salford, and Dr. Bertil Persso
Bibliographic record
Abstract
The Bioelectromagnetics Society announces the selection of 2010 Most Influential Bioelectromagnetics Journal Paper by Citation Award from among the primary research articles published between 2005 and 2009. It will be awarded to Dr. Igor Belyaev, Department of Genetics, Microbiology and Toxicology, Stockholm University, Stockholm, Sweden; Dr. Catrin Baureus Koch, Department of Radiation Physics and Department of Neurosurgery, Lund University Hospital, Lund, Sweden; Dr. Olle Terenius and Dr. Katarina Roxstrom-Lindquist, Department of Genetics, Microbiology and Toxicology, Stockholm University, Stockholm, Sweden; Dr. Lars Malmgren and Dr. Bertil Persson, Department of Radiation Physics, Lund University Hospital, Lund, Sweden; Dr. Wolfgang Sommer, Department of Neurotec, Karolinska Institutet, Stockholm, Sweden; and Dr. Leif Salford, Department of Neurosurgery, Lund University Hospital, Lund, Sweden, for their paper entitled, Exposure of rat brain to 915 MHz GSM microwaves induces changes in gene expression but not double stranded DNA breaks or effects on chromatin conformation, published in Bioelectromagnetics, vol 27(4): 295–306. May 2006. In addition to a certificate, the Award including a monetary prize will be presented in June 2011 to Dr. Belyaev, Dr. Baureus Koch, Dr. Terenius, Dr. Roxstrom-Lindquist, Dr. Malmgren, Dr. Sommer, Dr. Salford, and Dr. Persson during the Annual Scientific Meeting of the Bioelectromagnetics Society in Halifax, Canada. The Most Influential Bioelectromagnetics Journal Paper by Citation Award was established by the Bioelectromagnetics Society in 2007 to recognize scholarly contributions to the scientific community and to acknowledge and foster ongoing excellence in scientific discovery and achievement.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.180 | 0.155 |
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".