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Record W3033275033 · doi:10.3899/jrheum.200740

Rheumatologists and Pulmonologists at Temple University Weather the COVID-19 Storm Together

2020· letter· en· W3033275033 on OpenAlexvenueno aff
Roberto Caricchio, Gerard J. Criner

Bibliographic record

VenueThe Journal of Rheumatology · 2020
Typeletter
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsnot available
Fundersnot available
KeywordsRheumatologyMedicinePulmonologistsInternal medicineCoronavirus disease 2019 (COVID-19)Cytokine stormEditor in chiefPandemicFamily medicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Physical therapyDiseaseIntensive care medicineInfectious disease (medical specialty)Management

Abstract

fetched live from OpenAlex

In recent commentaries from Lancet Rheumatology and The Journal of Rheumatology 1,2, the authors eloquently illustrated the connection between the coronavirus disease 2019 (COVID-19) infection, the subsequent cytokine storm (CS) that ensues in a number of patients, and the potential efficacy of biologics that rheumatologists routinely use in their practices. Moreover, those biologics were originally investigated by rheumatologists for the treatment of numerous rheumatic conditions, including macrophage activating syndrome (MAS), a similar form of storm that resembles the one occurring in patients with COVID-193. The authors therefore conclude that rheumatologists could provide a helpful perspective in fighting the COVID-19 pandemic. The Thoracic Medicine and Surgery (TMS) Department and the Rheumatology Division at Temple University Hospital … Address correspondence to Dr. R. Caricchio, Temple University School of Medicine, 3322 N. Broad St., Philadelphia, PA 19140, USA. Email: roc{at}temple.edu.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
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 score0.148
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.295
Teacher spread0.245 · 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.

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

Citations6
Published2020
Admission routes1
Has abstractyes

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