Introduction to Ecology - A study on the relationship between hair colour and gender
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
Methods: In order to assess the relationship between hair colour and gender, 22 students enrolled in Ecology at York University were surveyed. Data was collected and entered into a Microsoft Excel spreadsheet.<br>Study Site: This study took place on September 15, 2016 in Room 118 of the Lumbers building at York University Keele Campus in Toronto, Ontario, Canada. <br>Hypothesis: There is no corelation between hair colour and gender because the genes that code for hair colour are not related to the genes that code for gender. <br>Predictions:<br>1) There will be no corelation between hair colour and gender because they are independent traits2) The distribution of hair colour will vary across males and females of different ethnicity and race3) Hair dyes can change someones natural hair colour coded by their genes <br>
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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