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Record W4200229367 · doi:10.5070/d3271055696

Calciphylaxis: how specific are the pathological features: avoiding false-positives and false-negatives

2021· article· en· W4200229367 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

VenueDermatology Online Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsUniversity of Alberta Hospital
Fundersnot available
KeywordsCalciphylaxisMedicinePathologicalFalse positive paradoxGold standard (test)False positives and false negativesPathologyIntensive care medicineIschemiaRadiologyCalcificationCardiology

Abstract

fetched live from OpenAlex

Calciphylaxis is considered a critical inflammatory dermatosis with potentially devastating clinical consequences. Skin biopsies are expedited for evaluation and are often considered as a gold standard for diagnostic confirmation and exclusion of other conditions. The key histopathological features include a combination of vascular and extra-vascular calcifications, intravascular microthrombi, and changes related to resulting ischemia. The pathological diagnosis of calciphylaxis is not always a straightforward process as it can be influenced by a number of factors. The specificity of pathological diagnosis of calciphylaxis has been questioned and a systematic approach with multidisciplinary collaboration is required to avoid potential errors.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.110
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.300
Teacher spread0.272 · 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