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Record W1975479012 · doi:10.1016/j.carj.2010.04.004

Serous Cystadenomas of the Pancreas: Long-term Follow-up Measurement of Growth Rate

2010· article· en· W1975479012 on OpenAlexaff
A. Ménard, George Tomlinson, Sean P. Cleary, Alice C. Wei, Steven Gallinger, Masoom A. Haider

Bibliographic record

VenueCanadian Association of Radiologists Journal · 2010
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsMount Sinai HospitalUniversity of TorontoUniversity Health NetworkToronto General HospitalSt. Michael's Hospital
Fundersnot available
KeywordsMedicineSerous CystadenomaSerous fluidLesionPopulationPancreasRadiologyKorean populationPathologyNuclear medicineInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: To measure the growth rate of microcystic subtype serous adenomas of the pancreas diagnosed by imaging. METHODS: For this retrospective study, 241 imaging studies were reviewed from 1998 to 2005. Thirty-one patients met our strict diagnostic imaging inclusion criteria and had at least 18 months of imaging follow-up. Patient demographics and lesion imaging characteristics were tested as predictors of growth. RESULTS: Growth was measured over a mean period of 42 months. There was a significant (P = .0004) linear growth of tumour for the population. There was significant clustering (P = .001) of the population into 2 growth rates: 0.50 mm/y (n = 23) and 5.5 mm/y (n = 8). The diameter of the lesion at presentation was significantly correlated with growth (r = 0.45; P = .01). CONCLUSION: The microcystic subtype of serous cystadenomas of the pancreas diagnosed with imaging criteria demonstrates 2 distinct and slow growth rates. The size of the lesion at presentation is correlated with growth rate.

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 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)0.004
metaresearch head score (Gemma)0.006
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 score0.048
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.028
GPT teacher head0.283
Teacher spread0.255 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2010
Admission routes1
Has abstractyes

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