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Record W2980861261 · doi:10.3899/jrheum.190823

Count of B-lines: A Matter with Persistent Limitations

2019· letter· en· W2980861261 on OpenAlexvenueno aff
Carla Maria Irene Quarato, Valeria Verrotti di Pianella, Marco Sperandeo

Bibliographic record

VenueThe Journal of Rheumatology · 2019
Typeletter
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLung ultrasoundParenchymaUltrasoundLungBeam (structure)Interstitial lung diseaseRadiologyNuclear medicineInternal medicinePathologyOpticsPhysics

Abstract

fetched live from OpenAlex

To the Editor: After reading the interesting review by Gutierrez, et al 1, entitled “Ultrasound in the assessment of interstitial lung disease in systemic sclerosis. A systematic literature review by the OMERACT Ultrasound Group,” we must take issue with some of the statements published. The authors state that “B-lines consist of ‘comet tails’… generated by the reflection of the [lung] US beam from thickened subpleural interlobar septa.” Actually, the generation of ultrasound (US) artifacts mainly depends on the high difference in acoustic impedance that the US beam encounters when it crosses surfaces with a different density. US scanner machines are calibrated at a constant sound speed of about 1500 m/s, but propagation velocity in air is only 330 m/s (in the lung, slightly increased to 440 m/s owing to presence of parenchyma): for this reason more than 96% of the US beam is reflected at tissue–chest wall/air-lung interface, resulting … Address correspondence to Dr. C.M. Quarato, Ospedali Riuniti di Foggia, Department of Respiratory Disease, Viale degli Aviatori 1, Foggia 71100, Italy. E-mail: c.quarato{at}libero.i

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.129
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.002
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 head0.051
GPT teacher head0.302
Teacher spread0.250 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations4
Published2019
Admission routes1
Has abstractyes

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