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Record W4389608026 · doi:10.26453/otjhs.1316356

Anatomical Variations in Fissure of the Lung on Computed Tomography

2023· article· en· W4389608026 on OpenAlexaff
Emre Emekli, Mesut Yıldırım

Bibliographic record

VenueOnline Türk Sağlık Bilimleri Dergisi · 2023
Typearticle
Languageen
FieldMedicine
TopicVascular anomalies and interventions
Canadian institutionsSAIT Polytechnic
Fundersnot available
KeywordsFissureMedicineComputed tomographyLungRadiological weaponRadiologyAnatomyInternal medicineGeology

Abstract

fetched live from OpenAlex

Objective: Lung fissures embryologically separate the bronchopulmonary segments from each other. We aimed to detect anatomical variations in fissures in patients who underwent thoracic computed tomography (CT). Materials and Methods: All the patients underwent a thoracic CT examination between July 1 - July 15, 2022. The patients’ gender, lung fissures continuity, accessory fissures presence, and variation side were recorded. The frequency of fissures was compared between the genders using the chi-square test. Results: The study included a total of 352 patients (211 men, 141 women). A total of 105 variations were detected in 95/352 (26.99%) of the patients, 61/211 (28.91%) were male, 34/141 (24.11%) were female. The right oblique fissure was incomplete in nine (2.6%), and the right horizontal fissure was incomplete in 14 (4%) patients and absent in 14 (4%). The left oblique fissure was observed to be incomplete in 16 (4.5%) patients. A total of 52 (14.8%) accessory fissures were detected. Conclusion: In the literature, a wide variety of fissure variations have been reported. Due to this diversity, having good knowledge of the fissure anatomical architecture is essential when performing surgical procedures and interpreting radiological images to clinically identify the location of bronchopulmonary segments.

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)0.000
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 score0.135
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.017
GPT teacher head0.301
Teacher spread0.284 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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