Doing Astronomy with Small Telescopes
Bibliographic record
Abstract
We are playing a lead role for growth of astronomy and its quality teaching and research in Manipur, a State located at northeast India (longitude = 93°58'E; latitude = 24°44'N; altitude = 782 m). We have innovatively designed and constructed three cost effective observatories, each costing a few hundred USD. These observatories are completely different in design and are perfectly usable for doing serious work on astronomical observation and measurements, using small ground-based telescopes. One Celestron CGE1400 telescope is housed with equatorial mounting in one of three constructed observatories and the same observatory has been inducted, since January 2012, as one of the members of the “Orion Project”, which is an international project headquartered at Phoenix, Arizona, USA, dedicated for photometric and spectroscopic observations of five bright variable stars of the Orion constellation. We have been producing high precision BVRI photometric data that match well with those produced by other observatories enrolled in the Orion project. Our photometric data were presented and discussed in the 33rd Annual Conference of the Society for Astronomical Sciences: Symposium on Telescope Science, held at Ontario, California, USA during June 12 - 14, 2014. Further, we could successfully demonstrate them to the entire population of the State and play live shows of the observation of three spectacular astronomical events namely, solar eclipse of 15th January 2010, lunar eclipse of 10th December 2011 and Transit of Venus of June 6, 2012. We have conducted a number of seminars and workshops for training and research in astronomy. In the present paper, we would like describe our self-built observatories, our observational facilities, the BVRI photometric data that we acquired for the Orion project, and other activities undertaken for growth of astronomy activities in the State of Manipur, India.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.042 | 0.024 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".