Grouping of Red Flour Beetles using two Different Strains
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
In this research project I studied how the Red Flour Beetle grouped over a 10 day time period with two different strains of the Beetle. One strain was the Canadian Red Flour Beetle and the other was the Manhattan, KS Red Flour Beetle. The grouping of the beetles is a behavior that is being tested in this experiment and can be greatly effected by both environment and genetics (Breed & Sanchez, 2010). Thus for this experiment I ask if different strains of the Red Flour Beetle aggregate differently and hypothesize that they will end up aggregating differently. After testing this question and hypothesis I found that The different strains do aggregate differently and this could be due to the different climates at which they are normally found. The Canadian lives in an overall lower temperature year round unlike the Kansas beetle (Baldwin & Fasulo, 2014). With this knowledge grain facilities will be able to better prevent infestations of this particular beetle (Gerken, Scully, &Campbell, 2018).
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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