Bibliographic record
Abstract
Edited by Scott I. Fairgrieve, 340 pp, with illus, Springfield, Ill, Charles C Thomas Ltd, 1999.This is a book of case studies on how skeletal analysis is applied to human and animal remains in medicolegal cases. The book probes the limits of forensic osteology and examines both successes and failures. The book does not teach the reader how to establish identification from skeletal remains, but rather supplies useful practical information about how actual skeletal analyses have been performed in a wide variety of cases.The 20 chapters, written by 32 contributors, cover the broad gamut of forensic identification, including identifying human versus animal bones, sex determination, DNA analysis, cremated remains, historical cases, facial reconstruction, video superimposition, detection of strangulation, unusual skeletal anomalies, mass disasters, and human rights investigations. Material on the use of insects in death investigation is also included. There is an excellent discussion of the pathologic changes seen on human skeletons before, during, and after death.The chapter on mass disasters discusses a collision between a passenger train and a freight train that occurred near Hinton, Alberta, Canada, in February 1986, resulting in 23 fatalities. The collision caused massive deformation of the passenger and freight cars with entrapment of the victims. An intense diesel fuel fire supplemented by spilled grain and sulfur from the freight cars hampered recovery efforts. Cold weather and large amounts of burned railcar insulation, which simulated burned bone, further complicated the process.The chapter on the role of forensic anthropology in human rights issues presents compelling information on the difficulties encountered in investigating genocide cases on foreign soil. Among the obstacles to the exhumation of a 1991 mass grave at Ovcara, Croatia, believed to contain as many as 200 remains, were land minds, explosives, and military and political intimidation. During a 1994 civil war in Rwanda, Hutu extremists killed 500 000 to 800 000 Tutsi. Forensic experts, including forensic anthropologists, archeologists, and pathologists from various parts of the world, participated in the recovery and analysis of the skeletal remains that resulted from the genocide in the vicinity of a church in Kibuye, Rwanda. Heat, explosives, poisonous snakes, and heavy vegetation made the work hazardous.The illustrations used in the book are of excellent quality, were carefully selected, and greatly facilitate understanding. Excellent references accompany each chapter. The book is primarily designed for students of forensic anthropology and presumes a background in human anatomy and osteology. Forensic pathologists and dentists who do identification work will also find this book very useful. The book provides an excellent overview of the field of forensic anthropology. It clearly delineates the potential contribution that can be made by the forensic anthropologist and archeologist in cases involving skeletal remains and encourages the early involvement of these specialists in the recovery of those remains.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.009 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".