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Record W3020098446 · doi:10.1186/s12943-020-01209-2

Analysis of the susceptibility of lung cancer patients to SARS-CoV-2 infection

2020· letter· en· W3020098446 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

VenueMolecular Cancer · 2020
Typeletter
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsMcMaster University
FundersChinese Academy of Medical Sciences Initiative for Innovative Medicine
KeywordsLung cancerAdenocarcinomaBiologyTMPRSS2LungCancerStage (stratigraphy)Internal medicineSerine proteaseCarcinomaGeneCancer researchImmunologyOncologyProteaseCoronavirus disease 2019 (COVID-19)EnzymeMedicineGeneticsDisease

Abstract

fetched live from OpenAlex

Recent studies have reported that COVID-19 patients with lung cancer have a higher risk of severe events than patients without cancer. In this study, we investigated the gene expression of angiotensin I-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) with prognosis in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Lung cancer patients in each age stage, subtype, and pathological stage are susceptible to SARS-CoV-2 infection, except for the primitive subtype of LUSC. LUAD patients are more susceptible to SARS-CoV-2 infection than LUSC patients. The findings are unanimous on tissue expression in gene and protein levels.

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)0.000
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 score0.154
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
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 head0.040
GPT teacher head0.391
Teacher spread0.351 · 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