Identity of victims from fragmented and decomposed remnants by DNA profiling in a case of serial killings
Bibliographic record
Abstract
A 28-year-old man, Surinder Koli, from a Nithari village adjoining Delhi, India committed serial murder. This case was of paramount importance in medico-legal investigations, as it was a landmark case of a serial killer reported from India. The skeletal remains (627 pieces) including skull/skull portions (19) were recovered from the nearby sewer drain, sump and the backyard of the house in which this man was residing. In addition, soft tissues (51) were also recovered from the same sewer drain. The victims were killed over a two-year period. The establishment of identity of the victims was crucial to prove the case in the court of law as well as for the claimants. Nineteen sets were prepared by radiology/anatomical examination from the exhibits recovered. DNA profiling confirmed the correctness of these sets and also short tandem repeat typing of nuclear DNA successfully identified eight individuals. Both DNA profiling and radiography/anatomical examination played an important role in solving this complicated case.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.077 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".