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Record W3204025012 · doi:10.1016/j.xpro.2021.100794

CloneSeq - Single-cell clonal 3D culture and analysis protocol

2021· article· en· W3204025012 on OpenAlexfundno aff
Xue Sun, Danny Bavli, Chen Kozulin, Alex Motzik, Amnon Buxboim, Oren Ram

Bibliographic record

VenueSTAR Protocols · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsnot available
FundersH2020 European Research CouncilIsraeli Centers for Research ExcellenceAzrieli FoundationIsrael Science FoundationEuropean Research CouncilHorizon 2020 Framework ProgrammeFP7 Coherent Development of Research Policies
KeywordsProtocol (science)Computational biologyAdaptation (eye)Sensitivity (control systems)Clonal selectionBiologyCellComputer scienceCell biologyGeneticsImmunologyMedicineNeuroscienceEngineering

Abstract

fetched live from OpenAlex

This CloneSeq protocol combines clonal expansion inside 3D hydrogel spheres and droplet-based RNA sequencing to resolve the limited sensitivity of single-cell approaches. CloneSeq can reveal rare subpopulations and support cellular stemness. CloneSeq can be adapted to different biological systems to discover rare subpopulations by leveraging clonal enhanced sensitivity. Important considerations include the hydrogel composition, adaptation of 3D cultured clones to the inDrops system, and inherent adhesive properties of the cells. CloneSeq is only validated for cell lines so far. For complete details on the use and execution of this protocol, please refer to (Bavli et al., 2021).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0040.003
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0450.051

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 head0.021
GPT teacher head0.285
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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

Citations4
Published2021
Admission routes1
Has abstractyes

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