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Record W2729342528 · doi:10.1016/j.dib.2017.06.046

Dataset of Sgo1 expression in cardiac, gastrointestinal, hepatic and neuronal tissue in mouse

2017· article· en· W2729342528 on OpenAlexafffund
Andrew T. Song, Antonella Galli, Séverine Leclerc, Stanley Nattel, Craig A. Mandato, Grégor Andelfinger

Bibliographic record

VenueData in Brief · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicATP Synthase and ATPases Research
Canadian institutionsUniversité de MontréalMontreal Heart InstituteMcGill UniversityCentre Hospitalier Universitaire Sainte-Justine
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchFonds de recherche du Québec
KeywordsBiologyImmunohistochemistryCerebellumGene expressionNeural tubeCell biologyGenePathologyNeuroscienceMedicineGeneticsImmunologyEmbryo

Abstract

fetched live from OpenAlex

The data shown in this article are related to the research article entitled “Characterization of Sgo1 expression pattern in developing and adult mouse” (Song et al., 2017) [3] . The article provides novel data on Sgo1 gene expression pattern utilizing Sgo1_LacZ_Knock in mouse line and immunohistochemistry in wild type mice. The data presents Sgo1 expression pattern during development, and in post-developmental proliferative and quiescent tissue. The article describes following tissues: developing heart, neural tube, adult colon, cerebellum, cerebral cortex, liver, and testis.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.006

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 head0.038
GPT teacher head0.348
Teacher spread0.309 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations7
Published2017
Admission routes2
Has abstractyes

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