Black Swans in ecology and evolution: The importance of improbable but highly influential events
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
The role of improbable but highly influential events in ecology and evolution is poorly understood. Recent works in economics and finance emphasize the importance that these events, so-called Black Swans, can have for the behavior, predictability and ultimately understanding of complex economic systems. Ecology and evolution are also complex systems that involve the interaction of organisms with their environment in different time scales and therefore they should also experience Black Swans. Here, we briefly discuss the nature of Black Swans, and their potential role in ecology and evolution. Traditionally, ecological and evolutionary research has been mostly focused in normal or regular events, while rare events have been usually ignored. However, several highly consequential events in ecology and evolution could qualify as Black Swans. For example, the sudden emergence of a new deadly pathogen, or, the rapid extinction or diversification of a lineage could be considered Black Swans. Thus, including the Black Swan phenomenon in ecological and evolutionary thinking may be necessary for a better understanding of these subjects.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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