Bibliographic record
Abstract
In astronomy, Very Long Baseline Interferometry (VLBI) is a powerful technique for exploring details of stars and galaxies at radio wavelength with unprecedented angular resolution.In order to realize VLBI using radio telescopes distributed in different regions and countries across oceans, the world-wide global collaboration is essential.Since 1967, when the first VLBI experiment was conducted in Canada, the progress of VLBI development has not been straightforward.VLBI is sometimes politics dependent since each radio telescope used for VLBI spans many countries based on different political systems.Recently, VLBI astronomers have come to the idea of creating an alliance for a "global array" and have begun organizing meetings to carry out.Thus, the international VLBI community seems to converge to the global array alliance to make only one largest radio telescope array in the world.In this short article, the current status of VLBI astronomy with some history and future prospects is briefly reviewed from my view points.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.028 | 0.042 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.011 | 0.023 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.014 |
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".