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Record W2909069340 · doi:10.3791/58709

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

2019· article· en· W2909069340 on OpenAlexafffund
Jo Anne Stratton, Sarthak Sinha, Wisoo Shin, Elodie Labit, Tak‐Ho Chu, Prajay Shah, Rajiv Midha, Jeff Biernaskie

Bibliographic record

VenueJournal of Visualized Experiments · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsHotchkiss Brain InstituteAlberta Children's HospitalUniversity of Calgary
FundersCanadian Institutes of Health ResearchChildren's Health Research InstituteUniversity of Calgary
KeywordsTranscriptomeBiologyCellComputational biologySingle-cell analysisCell biologyRNACell typeGene expressionGeneGenetics

Abstract

fetched live from OpenAlex

The analysis of single cell gene expression across thousands of individual cells within a tissue or microenvironment is a valuable tool for identifying cell composition, discrimination of functional states, and molecular pathways underlying observed tissue functions and animal behaviors. However, the isolation of intact, healthy single cells from adult mammalian tissues for subsequent downstream single cell molecular analysis can be challenging. This protocol describes the general processes and quality control checks necessary to obtain high-quality adult single cell preparations from the nervous system or skin that enabled subsequent unbiased single cell RNA sequencing and analysis. Guidelines for downstream bioinformatic analysis are also provided.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.793

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 head0.018
GPT teacher head0.325
Teacher spread0.307 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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
Published2019
Admission routes2
Has abstractyes

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