MétaCan
Menu
Back to cohort
Record W2889302188 · doi:10.1177/1925362118797729

Pathological Assessment of Chronic Traumatic Encephalopathy

2018· review· en· W2889302188 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

VenueAcademic Forensic Pathology · 2018
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsChronic traumatic encephalopathyPathologicalMedicineConcussionTraumatic brain injuryForensic pathologyAthletesHead traumaIntensive care medicineAutopsyPoison controlPathologyInjury preventionPsychiatryPhysical therapySurgeryMedical emergency

Abstract

fetched live from OpenAlex

Chronic traumatic encephalopathy (CTE) has become a topic of considerable interest in recent years, with wide-ranging implications for athletes, military members, and other groups exposed to frequent concussive or subconcussive head trauma. The condition has been subject to intensive neuropathological characterization by various groups, with assessment methodologies and staging criteria proposed. Clinical characterization of symptoms has also been performed, but has not yet been definitively formalized. While efforts are underway to develop in vivo markers of tauopathies including CTE, these remain experimental at this time, necessitating postmortem analysis for definitive diagnosis. The putative link between development of cognitive and behavioral dysfunction and neuropathological findings of CTE may prompt requests for postmortem assessment in the forensic setting. Here, we review current concepts in CTE research, describe histopathological findings in CTE, and describe methodologies for pathological assessment of CTE which may be useful to the forensic pathologist.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0030.004
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 head0.198
GPT teacher head0.473
Teacher spread0.275 · 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