The optical measurement speed of moving bodies and the observer's position effect
Bibliographic record
Abstract
From ancient times to the Newtonian mechanics system, people defaulted to the speed of light as infinity. People usually measure the speed of a moving object directly with the help of optical or electronic equipment and take the measured speed as the actual speed of the object. In fact, the speed of light is limited. When an object moves at high speed, we must correct the measured speed of the object. However, at present, people only use Einstein's special theory of relativity to deal with the high-speed motion of objects, and there is no theory to correct the measured speed of objects under the condition of high-speed motion. Here, we report that the optical measurement speed of an object is affected by the observer's position effect and obtain the relationship between the optical measurement speed and the actual speed. On this basis, this paper explains the reason why Newton's classical mechanics is suitable for the case of low-speed motion, and there is a large deviation between the optical measurement speed and the actual speed under the condition of high-speed motion. This paper also explains the velocity limit of high-energy particles and the phenomena of superluminal and negative velocity and analyzes the observation of microparticle motion. This paper provides a theory to explain and deal with the high-speed motion of objects, which is of great scientific significance.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".