EGO to ECO: Tracing the History of Radioecology from the 1950s to the Present Day
Bibliographic record
Abstract
This paper starts with a brief history of the birth of the field of radioecology during the Cold War with a focus on US activity. We review the establishment of the international system for radiation protection and the science underlying the guidelines. We then discuss the famous ICRP 60 statement that if "Man" is protected, so is everything else and show how this led to a focus in radioecology on pathways to "Man" rather than concern about impacts on environments or ecosystems. We then review the contributions of Radiation Research Society members and papers published in Radiation Research which contributed to the knowledge base about effects on non-human species. These fed into international databases and computer-based tools such as ERICA and ResRad Biota to guide regulators. We then examine the origins of the concern that ICRP 60 is not sufficient to protect ecosystems and discuss the establishment of ICRP Committee 5 and its recommendations to establish reference animals and plants. The review finishes with current concerns that reference animals and plants (RAPs) are not sufficient to protect ecosystems, given the complexity of interacting factors such as the climate emergency and discusses the efforts of ICRP, the International Union of Radioecologists and other bodies to capture the concepts of ecosystem services and ecosystem complexity modelling in radioecology.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".