Android Noahs and embryo Arks: ectogenesis in global catastrophe survival and space colonization
Bibliographic record
Abstract
Abstract To ensure long-term survival of humans and Earth life generally, strategies need to be in place to recolonize Earth after global catastrophes and to colonize exoplanets. In one strategy of space colonization, the physical barriers erected by time and space are circumvented by sending cryopreserved human and animal embryos to exoplanets rather than adult crews. There the embryos would be developed to neonates in artificial uterus (AU) systems. A similar strategy could also be used to repopulate Earth after human extinction events. In this paper, we review the status and future prospects of these embryonic survival strategies. A critical requirement in each scenario is an AU system for complete ectogenesis, i.e. complete development of embryos to neonates outside the natural womb. While such systems do not yet exist, they may soon be developed to afford clinical assistance to infertile women and reproductive choices to prospective parents. In human survival schemes, AU systems would likely first be used to extend conventional survival missions (e.g. subterranean bunkers) by replacing some adult crew members with cryopreserved embryos. For major mass extinctions and all far future events, adult crews would be entirely replaced by embryos and androids. The most advanced missions would feature orbiting embryo spacecraft for Earth recolonization and analogous interstellar spacecraft for colonizing exoplanets. We conclude that an advanced civilization using such an integrated, embryonic approach could eventually colonize distant parts of its home galaxy and potentially the wider universe.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".