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Record W2564363060 · doi:10.1097/rti.0000000000000251

The 100 Top-Cited Articles in Pulmonary Imaging

2016· article· en· W2564363060 on OpenAlexaboutno aff
Su Jin Hong, Kyoung Ja Lim, Hye Jeon Hwang, Sora Baek, Young Lan Seo, Eun Joo Yun, Chul Soon Choi, Dae Young Yoon

Bibliographic record

VenueJournal of Thoracic Imaging · 2016
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCitationSubject (documents)Pulmonary medicineWeb of scienceImpact factorScope (computer science)RadiologyMedical physicsLibrary sciencePathologyMeta-analysisLawComputer scienceIntensive care medicine

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study was to identify and characterize the 100 top-cited articles in pulmonary imaging. MATERIALS AND METHODS: From the database of Journal Citation Reports, 274 journals whose scope included pulmonary imaging were selected. The Web of Science search tools were then used to identify the 100 top-cited articles in the subject of pulmonary imaging published in these journals. The parameters used to analyze the characteristics of the 100 top-cited articles were journal (including subject category and impact factor), publication year, number of citations and annual citations, department and institution of authors, country of origin, article type, imaging technique, and topic. RESULTS: The 100 top-cited articles in pulmonary imaging were published between 1953 and 2012, with 43 published between 2000 and 2009. Citations ranged from 199 to 1447, and annual citations ranged from 5.1 to 314. The majority of articles were published in radiology or imaging journals (n=64), originated in the United States (n=49), were original articles (n=87), used computed tomography (n=66), and were based on the topic of pulmonary thromboembolism (n=18). Department of Radiology, Mayo Clinic (n=7), and Department of Radiology, University of British Columbia and Vancouver General Hospital (n=7), were the leading institutions, and Müller NL (n=11) was the most prolific author. CONCLUSIONS: Our study lists the 100 top-cited articles in pulmonary imaging, provides an insight into historical developments, and allows for recognition of advances in this field.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.198

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 head0.013
GPT teacher head0.335
Teacher spread0.322 · 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

Citations8
Published2016
Admission routes1
Has abstractyes

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