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Assessment of Intra‐ and Intercostal Variation in Rib Histomorphometry: Its Impact on Evidentiary Examination<sup>*</sup>

2007· article· en· W1971540445 on OpenAlexaff
Christian M. Crowder, Laura C. Rosella

Bibliographic record

VenueJournal of Forensic Sciences · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicForensic Anthropology and Bioarchaeology Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRib cageOsteonAnatomyPopulationThorax (insect anatomy)CadaverMedicineCortical bone

Abstract

fetched live from OpenAlex

Rib histological age estimation requires the evaluation of the middle third of the sixth rib. Human ribs have thin cortices and, when recovered, are often fragmented or absent, making it difficult to identify a specific midthoracic rib. This research explores the amount of microstructure variation in the middle third of the midthoracic ribs and determines whether the sixth rib age prediction equation can be applied to non-sixth ribs with similar accuracy. The amount of variability must be evaluated in order to meet the criterion for evidentiary examination. The sample consists of 120 cortical bone cross-sections from the middle third of ribs 3-8 removed from 20 cadavers. For each rib, osteon population densities (OPDs) and associated age estimates were calculated. The results demonstrate that non-sixth ribs can provide similar OPD values compared with those of the sixth ribs; however, individual variation proved to be significantly associated with bias, suggesting that individual factors influence the magnitude and direction of bias in non-sixth rib OPD values. This demonstrates the importance of evaluating multiple cross-sections (both intra- and inter-rib) to estimate age due to the normal remodeling variation within individuals.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.007
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 head0.033
GPT teacher head0.333
Teacher spread0.300 · 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 teacher head, not a consensus.

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

Citations36
Published2007
Admission routes1
Has abstractyes

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