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Record W2343614568 · doi:10.1111/1556-4029.13016

A Novel Forensic Investigation Applied to Bone Remains Exhumed near to Quirra Interforce Firing Range

2015· article· en· W2343614568 on OpenAlexaff
Luca Roncati, Antonietta Gatti, Federico Capitani, Goretta Bonacorsi, G Barbolini, Antonino Maiorana

Bibliographic record

VenueJournal of Forensic Sciences · 2015
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsCytodiagnostics (Canada)
Fundersnot available
KeywordsBone marrowScanning electron microscopeEnergy-dispersive X-ray spectroscopyMicroanalysisMaterials scienceNanotechnologyBiomedical engineeringPathologyMedicineChemistryComposite material

Abstract

fetched live from OpenAlex

The need to implement novel techniques, able to support a causal link between exposure and pathology, has been emerged over the recent years. The application of scanning electron microscope coupled with probe X-ray microanalysis (by means of an energy-dispersive spectroscopy) has been developed by our research group for the bone remains investigation. It was aimed to testify the exposure to microsized and nanosized pollutions, due to military activities in the Quirra interforce firing range, of a Sardinian shepherd, died of acute leukemia. Metallic debris with a combustive morphology and with an oncogenic potential has been surely detected inside his bone marrow canal. This novel technique has proved to be able to bring to light a source of past exposure preserved over time within the bone marrow canal. It can be useful for postmortem analyses, delivering a new avant-garde approach to modern forensic science.

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

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.072
GPT teacher head0.304
Teacher spread0.232 · 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

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2015
Admission routes1
Has abstractyes

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