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Record W2050218188 · doi:10.1016/j.neuron.2012.06.033

How Variable Clones Build an Invariant Retina

2012· article· en· W2050218188 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

VenueNeuron · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsUniversité de MontréalMontreal Clinical Research Institute
FundersWellcome TrustEngineering and Physical Sciences Research CouncilU.S. Department of Energy
KeywordsBiologyLineage (genetic)Progenitor cellRetinaNeuroscienceCell fate determinationProgenitorZebrafishCellular differentiationCell typeTranscription factorCell biologyGeneticsStem cellCellGene

Abstract

fetched live from OpenAlex

A fundamental question in developmental neuroscience is how a collection of progenitor cells proliferates and differentiates to create a brain of the appropriate size and cellular composition. To address this issue, we devised lineage-tracing assays in developing zebrafish embryos to reconstruct entire retinal lineage progressions in vivo and thereby provide a complete quantitative map of the generation of a vertebrate CNS tissue from individual progenitors. These lineage data are consistent with a simple model in which the retina is derived from a set of equipotent retinal progenitor cells (RPCs) that are subject to stochastic factors controlling lineage progression. Clone formation in mutant embryos reveals that the transcription factor Ath5 acts as a molecular link between fate choice and mode of cell division, giving insight into the elusive molecular mechanisms of histogenesis, the conserved temporal order by which neurons of different types exit the cell cycle.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score0.402

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 head0.011
GPT teacher head0.225
Teacher spread0.214 · 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