"Gravitational Waves" by Dmytro Poliak. Analysis of data from gravitational wave signals on gravitational interferometers. Search for sources of gravitational waves in the visible range.
Bibliographic record
Abstract
INTRODUCTION In the introduction, I have chosen to elucidate why I opted for this particular topic. Relevance As I have previously mentioned, there is much to contemplate, and perhaps this became the primary reason. In this work, I will convey all the known information about gravitational waves, encompassing theories and assumptions, and I will also conduct a data analysis. For a deeper understanding of this topic, I have joined the GRANDMA project, which investigates the nature of gravitational waves at a highly advanced level. I believe that gravitational waves represent a new trend in contemporary and future astrophysics. Gravitational waves are an extraordinarily intriguing object that demands observation. Thanks to gravitational waves, we can discover new astronomical objects. Additionally, gravitational waves have been instrumental in reaffirming numerous scientific theories, such as the general theory of relativity and the theory of the big bang. I am of the opinion that gravitational waves will assist us in better comprehending the Universe, and perhaps even draw scientists closer to the creation of new theories (such as the theory of everything). Objective: Analysis of data from gravitational wave signals on gravitational interferometers. Search for sources of gravitational waves in the visible range. Tasks: 1. Analyze all data on gravitational waves known at the moment. 2. Extract parameters of gravitational waves necessary for their registration. 3. Participate in the program to search for sources of gravitational waves in the visible range. Research Object: Gravitational waves. Subject of Research: Detection of gravitational waves, search for their sources in the visible range. Research Methods: Analysis and systematization of theoretical data, comparison, observation of galaxies. Scientific Novelty: Gravitational waves were first directly detected in 2016. Also, in this work, I have formulated my own perspective on certain theoretical aspects of gravitational wave research. Practical Value: Participated in the international company for the search and research of gravitational wave sources - GRANDMA.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.057 |
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".