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Record W4410443544 · doi:10.1101/2025.05.13.653297

Empowering medaka fish biology with versatile genomic resources in MedakaBase

2025· preprint· en· W4410443544 on OpenAlexfundno aff
Kenji Morikami, Yasuhiro Tanizawa, Masaru Yagura, Mika Sakamoto, Shoko Kawamoto, Yasukazu Nakamura, Katsushi Yamaguchi, Shuji Shigenobu, Kiyoshi Naruse, Satoshi Ansai, Shigehiro Kuraku

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsnot available
FundersNational Institute for Basic BiologyInstitute of Genetics
KeywordsFish <Actinopterygii>BiologyComputational biologyEvolutionary biologyFishery

Abstract

fetched live from OpenAlex

Abstract Medaka, a group of small, mostly freshwater fishes in the teleost order Beloniformes, includes the rice fish Oryzias latipes , which is a prominent model organism for diverse biological fields. Chromosome-scale genome sequences of the Hd-rR strain of this species were obtained in 2007, and its improved version has facilitated various genome-wide studies. However, despite its widespread utility, omics data for O. latipes are dispersed across various public databases and lack a centralized platform. To address this, the medaka section of the National Bioresource Project (NBRP) of Japan established a genome informatics team in 2022 tasked with providing versatile in silico solutions for bench biologists. This initiative led to the launch of MedakaBase ( https://medakabase.nbrp.jp ), a web server that enables gene-oriented analysis including exhaustive sequence similarity searches. MedakaBase also provides genome-wide browsing of diverse datasets, including tissue-specific transcriptomes and intraspecific genomic variations, integrated with gene models from different sources. Additionally, the platform offers gene models optimized for single-cell transcriptome analysis, which often requires coverage of the 3′ untranslated region (UTR) of transcripts. Currently, MedakaBase provides genome-wide data for seven Oryzias species, including original data for O. mekongensis and O. luzonensis produced by the NBRP team. This article outlines technical details behind the data provided by MedakaBase.

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 categoriesMeta-epidemiology (narrow)
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 score0.179
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0010.000
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 head0.012
GPT teacher head0.251
Teacher spread0.239 · 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.

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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicIdentification and Quantification in FoodFrench-language works237,207