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Record W7018462879

Diagnostic Performance of a Prototype Dual-energy Chest Imaging System

2011· dissertation· en· W7018462879 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2011
Typedissertation
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsRadiographyNodule (geology)Digital radiographyDual energyLungLung biopsyReceiver operating characteristicStage (stratigraphy)
DOInot available

Abstract

fetched live from OpenAlex

Purpose: To assess the performance of a Dual-Energy chest radiography system.\nMethods: A cohort of 129 patients was recruited from population referred for CT guided biopsy of a lung lesion. Digital radiography (DR) and Dual Energy (DE) images were acquired. Receiver operating characteristic (ROC) tests were performed to evaluate performance of DE images compared to DR. Five chest radiologists scored images. Performance was analyzed for all cases pooled and sub groups based on gender, nodule size, density, location, and chest diameter.\nResults: There was no significant difference between DE and DR for all cases (p = 0.61). There was a significant advantage for DE imaging of small nodules, and nodules located in right-upper lobe. (p = 0.02 and 0.01)\n\nConclusions: DE imaging demonstrated significant improvement in diagnosis of sub-centimeter lung nodules and lesions in the upper lung zones which are common characteristic of early stage lung malignancy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.002
GPT teacher head0.125
Teacher spread0.124 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2011
Admission routes1
Has abstractyes

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Same venueLibrary and Archives Canada (Government of Canada)Same topicAdvanced X-ray and CT ImagingFrench-language works237,207