Learning More About Earthworms With Citizen Science
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Have you ever wanted to conduct scientific research? Citizen, or community science involves non-scientists in assisting scientists with research. The term covers a huge variety of projects: from online-only where you can classify galaxies, to practical outdoor activities, and even helping with scientific expeditions. Ideally, citizen science benefits everyone—scientists collect more data, and over larger geographic areas than they could on their own. Non-scientists benefit by learning something new and experiencing how science works, and hopefully having fun! The small size of most soil organisms is challenging for citizen science. However, earthworms are easy to recognize and relatively large, so there have been several citizen science projects focused on them. In this article, we discuss earthworm citizen science from its origins with 18th and 19th century natural historians, to the modern day. Discover what non-scientists have contributed to earthworm science and how you can design your own earthworm investigations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it