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Record W2099038667 · doi:10.5489/cuaj.11135

Guidelines for the management of the incidentally discovered adrenal mass

2011· article· en· W2099038667 on OpenAlex
Anil Kapoor, Topher Morris, Ryan Rebello

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Urological Association Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicAdrenal and Paraganglionic Tumors
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

With advances in modern imaging technology, the presentation of an incidentally found adrenal mass (or incidentaloma) has become an increasingly common management scenario for endocrinologists and urologists. The prevalence of adrenal incidentalomas (AI) has been reported as high as 8% in autopsy series and 4% in radiologic series.1,2 As improved imaging techniques become available and the frequency of abdominal imaging increases, the radiologic prevalence is expected to continue escalating, approaching the autopsy series. Also concerning is the evidence supporting an increased prevalence with age, with the risk of finding an AI being more common in the later years of life.3 In a rapidly aging society, the diagnosis and management of AI will become a more frequent task. As such, guidelines are useful to guide appropriate treatment.

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)0.000
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 score0.165
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.055
GPT teacher head0.274
Teacher spread0.219 · 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