Planetary Biosecurity: Applying Invasion Science to Prevent Biological Contamination from Space Travel
Bibliographic record
Abstract
Abstract As plans for space exploration and commercial use expand rapidly, biosecurity measures and risk assessments that inform them must adapt. Sophisticated protocols are required to prevent biological contamination of extraterrestrial environments from Earth and vice versa. Such protocols should be informed by research on biological invasions—human-assisted spread of organisms into novel environments—which has revealed, inter alia, that (1) invasion risk is driven by the timing and frequency of introduction events, whose control requires addressing the least secure human activities associated with organismal transport; (2) invasions and their impacts are difficult to predict, because these phenomena are governed by context dependencies involving traits of the organism and the receiving environment; and (3) early detection and rapid response are crucial for prevention but undermined by taxonomic methods that fail to recognize what is “alien” versus what is native. Collaboration among astrobiologists, invasion biologists, and policymakers could greatly enhance planetary biosecurity protocols.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".