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Record W4286511916 · doi:10.1016/j.xpro.2022.101617

Infecting kidney organoids with a cDNA reporter clone of SARS-CoV-2

2022· article· en· W4286511916 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSTAR Protocols · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchUniversity of Texas Medical Branch at Galveston
KeywordsOrganoidInduced pluripotent stem cellclone (Java method)BiologyComplementary DNAKidneyVirologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)HEK 293 cellsCell biologyCell cultureCoronavirus disease 2019 (COVID-19)Molecular biologyInfectious disease (medical specialty)MedicinePathologyDNAGeneGenetics

Abstract

fetched live from OpenAlex

Induced pluripotent stem cell (iPSC)-derived kidney organoids can be used for disease modeling and drug testing. Here, we describe a protocol to prepare stocks of an infectious clone of SARS-CoV-2 expressing a stable mNeonGreen reporter (icSARS-CoV-2-mNG). We demonstrate the infection of kidney organoids, primarily at the proximal tubular cells, with icSARS-CoV-2-mNG. Using a TCID50 (tissue culture infectious dose 50) assay and confocal microscopy, we show the quantification of SARS-CoV-2-mNG signal in proximal tubular cells of the kidney organoids. For complete details on the use and execution of this protocol, please refer to Rahmani et al. (2022).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.017
GPT teacher head0.295
Teacher spread0.278 · 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