Millikan's Oil-Drop Experiment: A Centennial Setup Revisited in Virtual World
Bibliographic record
Abstract
Early in the last century, Robert Millikan developed a precise method of determining the electric charge carried by oil droplets.1–3 Using a microscope and a small incandescent lamp, he observed the fall of charged droplets under the influence of an electric field inside a small observation chamber. In so doing, Millikan demonstrated the existence of a fundamental unit of electric charge, and established its quantization. Now renowned as one of the most famous experiments of 20th-century physics, Millikan's oil-drop experiment has been reproduced with more or less success in most, if not all, high school and university physics classes. This has encouraged many improvements of the apparatus, now making this experiment much more accurate and easier to realize for advanced students. However, the required apparatus remains rather expensive, and for introductory college or high school students the experiment is still quite difficult to conduct. As an alternative to the traditional setup, a realistic computer-based simulator to replicate the Millikan oil-drop experiment has been developed. Using this software, students are able to undertake a complete experiment, obtain an accurate set of results, and thus gain a better understanding of the original experiment and its historical importance.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".