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Record W4414494573 · doi:10.5744/fa.2025.0012

Turhon A. Murad

2025· article· en· W4414494573 on OpenAlexaff
Melanie M. Beasley, Eric J. Bartelink, Amy Z. Mundorff, Ben Figura

Bibliographic record

VenueForensic Anthropology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsOffice of the Chief Medical Examiner
Fundersnot available
KeywordsCertificateState (computer science)BiographyIdentification (biology)Forensic science

Abstract

fetched live from OpenAlex

Dr. Turhon A. Murad was the first tenure-track biological anthropologist hired at California State University, Chico (Chico State). He founded the Human Identification Laboratory in 1974, became the 42nd Diplomate of the American Board of Forensic Anthropology in 1989, started the Chico State Certificate in Forensic Identification in 1995, and was active in forensic casework for 40 years. Turhon had a long, successful career as a professor and forensic anthropologist and was influential in the careers and lives of countless students, many of whom became forensic anthropologists. This biography was developed from discussions among the coauthors, all of whom were mentored by Turhon as master’s students. We highlight his key accomplishments, contributions to the field, and the role he played as a mentor and friend. While Turhon sometimes felt like an outsider in the field, given that his academic lineage was outside of forensic anthropology, he was tremendously proud of his students’ accomplishments and the strong program he helped build at Chico State.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.883
Threshold uncertainty score0.390

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1170.038

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 head0.329
Teacher spread0.315 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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