Tying Anomalies and their Significance in Analysing Knot Evidence
Bibliographic record
Abstract
Most people tie Granny or Reef Knots, which contain pairs of identical or opposite Half Knots, respectively. The exact configuration of these knots could be significant when found at crime scenes. A survey of 562 volunteers revealed that a minority tie noteworthy anomalies that differ from this common trend. When asked to tie shoelace and parcel knots, 70 respondents produced anomalies. Of particular significance was the fact that 3% of respondents—19 out of 528 who completed the survey tasks—produced Figure Eight and Figure Nine Hitches in combination with normal Half Knots. The act of tying a bow may be an important factor in the generation of anomalous hitches because 15 out of 19 survey anomalies containing either a Figure Eight or Figure Nine Hitch occurred in the shoelace samples. Figure Eight and Figure Nine Hitches may be rarer in homicide ligatures because only four out of those 19 survey anomalies were parcel knots, which are similar to crime scene knots. There are at least 64 possible combinations of paired Half Knots and Figure Eight or Figure Nine Hitches. Although not unique, these unusual tying configurations are noteworthy and could reduce the field of possible knot tiers during criminal investigations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.215 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".