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Record W2071185380 · doi:10.1097/rct.0b013e3181fba8c4

Magnetic Resonance Imaging Sialolithography

2011· article· en· W2071185380 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

VenueJournal of Computer Assisted Tomography · 2011
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster University
FundersNational Institute of General Medical Sciences
KeywordsMedicineMagnetic resonance imagingRadiologySalivary Gland DiseasesSialadenitisNuclear magnetic resonanceSubmandibular glandPhase imagingNuclear medicineSalivary glandPathologyMicroscopy

Abstract

fetched live from OpenAlex

Magnetic resonance imaging (MRI) sialolithography is a useful technique for evaluating acute and chronic sialadenitis. However, its major weakness is that stones are not imaged directly. We have developed an MRI technique that allows specific identification and localization of calculi within the submandibular salivary gland or duct. This test is noninvasive and does not require ionizing radiation or a sialogogue. By using 3-dimensional susceptibility-weighted imaging, one can probe MRI signal phase changes. Corrected positive filtered phase and magnitude images, acquired using susceptibility-weighted imaging, allowed identification and anatomical localization of calcified calculi in the submandibular gland with efficacy comparable to computed tomography.

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 score0.077
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
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 head0.020
GPT teacher head0.243
Teacher spread0.223 · 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