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Record W4415586623 · doi:10.1038/s41598-025-21196-y

Proximal phalanges of digit 1 have different identities in the forelimbs and hindlimbs of the mouse

2025· article· en· W4415586623 on OpenAlexaff
Wanyi Dang, Ziqiu Jia, Junnan Chen, Jialong Yin, Shibin Bai, David M. Irwin, Shuyi Zhang, Zhe Wang

Bibliographic record

VenueScientific Reports · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender Studies in Language
Canadian institutionsUniversity of Toronto
FundersDepartment of Science and Technology of Liaoning Province
KeywordsNumerical digitPhalanxForelimbHindlimbProximal phalanx

Abstract

fetched live from OpenAlex

Mice possess hands and feet similar to humans including two phalanges for digit 1 and three phalanges in digits 2 to 5. The phalanges that make up the digits were named by their positions, however, phalanx identities between digits are unconfirmed by genetic evidence. Here we show that the proximal phalanges of digit 1 of the fore- and hindlimbs have different identities compared to the phalanges of digit 2. We found strong signals from mRNA-Seq results that unite the proximal phalanx of forelimb digit 1 with the proximal phalanx of forelimb digit 2, while the proximal phalanx of hindlimb digit 1 groups the middle phalanx of hindlimb digit 2. The same result was obtained when other clustering methods were used, indicating that our results are robust. Our results demonstrate that there are developmental differences among phalanges and that the proximal phalanx identities of digit 1 differ between the fore- and hindlimbs of the mouse.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.295
Teacher spread0.278 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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