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Record W2593127589 · doi:10.1016/j.ijpp.2017.02.002

Neoplasm or not? General principles of morphologic analysis of dry bone specimens

2017· article· en· W2593127589 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Paleopathology · 2017
Typearticle
Languageen
FieldDentistry
TopicOral and Maxillofacial Pathology
Canadian institutionsWestern University
Fundersnot available
KeywordsDifferential diagnosisPathologyRadiographyMedicineNeoplastic diseaseAnatomyRadiology

Abstract

fetched live from OpenAlex

Unlike modern diagnosticians, a paleopathologist will likely have only skeletonized human remains without medical records, radiologic studies over time, microbiologic culture results, etc. Macroscopic and radiologic analyses are usually the most accessible diagnostic methods for the study of ancient skeletal remains. This paper recommends an organized approach to the study of dry bone specimens with reference to specimen radiographs. For circumscribed lesions, the distribution (solitary vs. multifocal), character of margins, details of periosteal reactions, and remnants of mineralized matrix should point to the mechanism(s) producing the bony changes. In turn, this allows selecting a likely category of disease (e.g. neoplastic) within which a differential diagnosis can be elaborated and from which a favored specific diagnosis can be chosen.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.060
GPT teacher head0.352
Teacher spread0.292 · 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