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Record W3214175100 · doi:10.1126/sciadv.abj9846

Phase transition specified by a binary code patterns the vertebrate eye cup

2021· article· en· W3214175100 on OpenAlexaff
Revathi Balasubramanian, Xuanyu Min, Peter M. J. Quinn, Quentin Lo Giudice, Chenqi Tao, Karina Polanco, Neoklis Makrides, John Peregrin, Michael Bouaziz, Yingyu Mao, Qian Wang, Bruna Lopes da Costa, Diego F. Buenaventura, Fen Wang, Liang Ma, Stephen H. Tsang, Pierre J. Fabre, Xin Zhang

Bibliographic record

VenueScience Advances · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDevelopmental Biology and Gene Regulation
Canadian institutionsColumbia College
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Diabetes and Digestive and Kidney DiseasesNational Eye InstituteNational Institute on AgingNational Institutes of Health
KeywordsVertebrateBinary numberCode (set theory)Computer sciencePhase (matter)Transition (genetics)Phase transitionBinary codeBiologyMathematicsPhysicsProgramming languageGeneticsArithmeticSet (abstract data type)

Abstract

fetched live from OpenAlex

The developing vertebrate eye cup is partitioned into the neural retina (NR), the retinal pigmented epithelium (RPE), and the ciliary margin (CM). By single-cell analysis, we showed that fibroblast growth factor (FGF) signaling regulates the CM in its stem cell–like property of self-renewal, differentiation, and survival, which is balanced by an evolutionarily conserved Wnt signaling gradient. FGF promotes Wnt signaling in the CM by stabilizing β-catenin in a GSK3β-independent manner. While Wnt signaling converts the NR to either the CM or the RPE depending on FGF signaling, FGF transforms the RPE to the NR or CM dependent on Wnt activity. The default fate of the eye cup is the NR, but synergistic FGF and Wnt signaling promotes CM formation both in vivo and in human retinal organoid. Our study reveals that the vertebrate eye develops through phase transition determined by a combinatorial code of FGF and Wnt signaling.

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 score0.037
Threshold uncertainty score0.204

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 head0.009
GPT teacher head0.289
Teacher spread0.280 · 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

Citations33
Published2021
Admission routes1
Has abstractyes

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