Intérêt de l'analyse des isotopes stables en identification médico-légale: Exemple du carbone 13
Bibliographic record
Abstract
ResumeL'identification medico-legale d'une victime repose sur l'etude de caracteristiques specifiques a chaque individu (empreintes digitales et genetiques). Cependant, il est parfois impossible d'acceder a ces donnees du fait de la degradation importante du corps (carbonisation, etc.). Quant a l'odontologie medico-legale, son interet achoppe sur l'absence d'informations ante mortem a comparer aux indices post-mortem. Dans ces cas la, l'analyse des isotopes stables, notamment le carbone 13, peut s'averer un outil puissant au service de l'identification medico-legale. La caracterisation isotopique, si elle n'est pas specifique a un individu, est la transcription chimique de la vie de cet individu, notamment de son alimentation et de son lieu de vie. L'etude de differents tissus humains permet egalement de tracer les migrations d'un individu au cours de son existence, depuis les dents qui fournissent des informations sur l'enfance de la victime jusqu'aux cheveux refletant ses dernieres annees de vie. Ces in...
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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 | 0.002 | 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 | 0.005 | 0.112 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".