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Record W4407447953 · doi:10.1126/science.adp3411

Evolutionary convergence of sensory circuits in the pallium of amniotes

2025· article· en· W4407447953 on OpenAlexaff
Eneritz Rueda-Alaña, Rodrigo Senovilla-Ganzo, Marco Grillo, Enrique Vázquez, Sergio Marco Salas, Tatiana Gallego‐Flores, Aitor Ordeñana-Manso, Artemis Ftara, Laura Escobar, Alberto Benguría, Ana Quintas, Ana Dopazo, Miriam Rábano, María dM Vivanco, Ana M. Aransay, Daniel Garrigos, Ángel Toval, José Luis Ferrán, Mats Nilsson, Juan Manuel Encinas, Maurizio De Pittà, Fernando García‐Moreno

Bibliographic record

VenueScience · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsAmnioteBiologySensory systemGlutamatergicNeuroscienceBiological neural networkSensory processingEvolutionary biologyVertebrateGeneGlutamate receptor

Abstract

fetched live from OpenAlex

The amniote pallium contains sensory circuits that are structurally and functionally equivalent, yet their evolutionary relationship remains unresolved. We used birthdating analysis, single-cell RNA and spatial transcriptomics, and mathematical modeling to compare the development and evolution of known pallial circuits across birds (chick), lizards (gecko), and mammals (mouse). We reveal that neurons within these circuits' stations are generated at varying developmental times and brain regions across species and found an early developmental divergence in the transcriptomic progression of glutamatergic neurons. Our research highlights developmental distinctions and functional similarities in the sensory circuit between birds and mammals, suggesting the convergence of high-order sensory processing across amniote lineages.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.013
GPT teacher head0.262
Teacher spread0.249 · 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 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

Citations29
Published2025
Admission routes1
Has abstractyes

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