Study of the Correlation Between an Individual's Hair Colour and Gender Using a Verbal Survey
Why this work is in the frame
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Bibliographic record
Abstract
Methods: In order to examine the relationship between an individual's hair colour and their gender, a verbal study of 24 students was conducted. <br>Study Site: The study took place indoors, in a laboratory at York University, located in Toronto, Canada. No equipment was used.<br>Hypothesis: It was hypothesized that there would be no correlation between hair colour and gender, because the genes that code for each respective phenotype are separate.<br>Predictions:1) Hair colour and gender will be independent of each other.2) There will not be any pattern of either male or female students having a particular hair colour.3) Whether any correlation exists between hair colour and gender will be difficult to examine as an individual's natural hair colour is easily altered by the use of hair dyes.
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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 | 0.000 |
| 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) | 0.027 | 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