MétaCan
Menu
Back to cohort

Évaluation de la Date D'Un Tir

2007· article· fr· W2332068127 on OpenAlexvenueno aff
BenoÎT Persin, Patrick Touron, Fabien Mille, Gilles Bernier, Thierry Subercazes

Bibliographic record

VenueCanadian Society of Forensic Science Journal · 2007
Typearticle
Languagefr
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsForestryHumanitiesArtGeography

Abstract

fetched live from OpenAlex

RÉSUMÉUne méthode permettant de dater un tir est présentée. La technique analytique est décomposée en deux étapes: d'abord un prélèvement par microextraction en phase solide (SPME) à l'intérieur du canon d'un fusil de chasse, suivi d'une analyse par chromatographie en phase gazeuse couplée à un détecteur à ionisation de flamme (GC/FID) ou à un spectromètre de masse (GC/MS). Des produits typiques résultant d'une combustion incomplète ont été détectés et dix d'entre eux ont été identifiés comme étant des hydrocarbures polycycliques aromatiques (HPA). L'analyse simultanée de quatre de ces HPA (naphtalène, 1-méthyl naphtalène, 2-méthyl naphtalène et acénaphtylène) confirme que le fusil de chasse suspecté a tiré récemment, quel que soit le couple munition-arme. L'évaluation de la date du tir est basée sur le taux d'échappement de ces HPA hors du canon du fusil. Une mesure quotidienne de l'aire du pic de naphtalène peut permettre une évaluation de la date d'un tir sous certaines conditions. Tout d'abord, l'origine des HPA sera examinée en étudiant différentes munitions. Puis, la technique analytique sera expliquée avant l'étude de différents paramètres, telles les conditions environnementales lors du tir, la longueur des canons et leur obturation, la présence de lubrifiant et enfin, le nombre de tir.

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.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.240
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designBench or experimental · Other design
Domainnot available
GenreMethods · Empirical

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".

Quick stats

Citations12
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Society of Forensic Science JournalSame topicEnergetic Materials and CombustionFrench-language works237,207