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
Fingernails submitted in criminal cases involving struggles between individuals may contain trace evidence linking the two parties. Fingernail clippings can be examined for the presence of fibres and, if present, these fibres can be compared to the fibres used in the construction of a particular garment. The significance of finding fibres on clippings and the frequency of finding specific fibres are important issues in the ability to form a meaningful forensic conclusion. Fingernail clippings from fifty-six subjects were examined for the presence of fibres. The fibres were categorized according to colour and type (cottons, wools, other naturals and manmade). The subjects were classified according to gender, age, and left versus right handed dominance. It was determined that it was not unusual to find fibres under fingernails and that colourless/white, blue, and grey/black cottons were the most predominant. No significant differences were identified with respect to gender of the subjects. No trend emerged that illustrated a tendency for the number of recovered fibres to be related to the dominant hand. Children had more fibres under their nails than adults.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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