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Record W3174703119 · doi:10.30574/gscarr.2021.7.3.0035

High resolution computed tomography signs lead an early diagnosis of COVID-19

2021· article· en· W3174703119 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGSC Advanced Research and Reviews · 2021
Typearticle
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsASTER
Fundersnot available
KeywordsRadiological weaponMedicineCoronavirus disease 2019 (COVID-19)Computed tomographySigns and symptomsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)RadiologyClinical significanceDiseaseInternal medicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Introduction: The novel coronavirus disease 2019 (COVID-19) has huge impact on public health. RT-PCR of respiratory samples is generally accepted confirmatory test which can miss several cases due to various factors. Case description: A 32-years-old male without any co-morbidity presented with complaints of cough and fever was negative for Reverse Transcription Polymerase Chain Reaction (RT-PCR) on two separate occasions on two different centres died and the last sample sent on 30th day of admission tested positive for RT-PCR. Radiologist reported the CT Chest signs as highly likely case of COVID-19 on the day of admission. Clinical significance: Radiological signs on CT chest can contribute in the diagnostic workup of CIVID-19. Conclusion: Radiological signs reported in suspected COVID-19 should be noticed and given adequate weightage in conditions where the other laboratory tests are negative.

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.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.087
GPT teacher head0.429
Teacher spread0.342 · 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