Searching for Extraterrestrial Intelligence by Locating Potential ET Communication Networks in Space
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
There have been periodic efforts in recent decades to search for extraterrestrial intelligence (SETI), especially by trying to find an extraterrestrial (ET) radio signal or other technosignature in space. Yet, no such technosignatures have been found. Considering the vastness of space, finding such technosignatures has been described as trying to find a needle in a cosmic haystack. To help resolve this, two hypotheses are proposed to aid SETI researchers in narrowing the search for ET technosignatures, based on a network analysis approach to locate where in space potential ET communication networks would most likely be. A potential ET communication network can use exoplanets as communication access points (e.g., placing a communication satellite into planetary orbit, or an antenna on a planetary surface). The approach uses a topology where exoplanets are represented as nodes, and the lines of average distance (generalized communication paths) between adjacent exoplanets are represented as edges; the nodes and edges form local and wide planetary networks. Using the approach and data visualization on exoplanet databases can highlight locations of potential ET communication networks in space. The first hypothesis posits that an ET technosignature would more likely appear in a potentially habitable solar system containing a high concentration of planets, wherein the planets function as communication access points to facilitate a potential ET communication network. The second hypothesis posits that an ET technosignature would more likely appear in a highly concentrated cluster of potentially habitable solar systems. Contributions to the SETI field can be increased accuracy in finding ET technosignatures, increased accuracy in reaching a Schelling point (a mutual realization of how we and an ET intelligence can find each other), and promoting interdisciplinary SETI research.
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.
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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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