MétaCan
Menu
Back to cohort
Record W3042149895 · doi:10.1002/jez.b.22978

Dark world rises: The emergence of cavefish as a model for the study of evolution, development, behavior, and disease

2020· article· en· W3042149895 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Experimental Zoology Part B Molecular and Developmental Evolution · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSubterranean biodiversity and taxonomy
Canadian institutionsMount Saint Vincent University
FundersNational Institute of Dental and Craniofacial ResearchNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyEvolutionary biologyTraitDiversity (politics)Model organismGeneticsAnthropologyGeneSociologyComputer science

Abstract

fetched live from OpenAlex

A central question in biology is how naturally occurring genetic variation accounts for morphological and behavioral diversity within a species. The Mexican tetra, Astyanax mexicanus, has been studied for nearly a century as a model for investigating trait evolution. In March of 2019, researchers representing laboratories from around the world met at the Sixth Astyanax International Meeting in Santiago de Querétaro, Mexico. The meeting highlighted the expanding applications of cavefish to investigations of diverse aspects of basic biology, including development, evolution, and disease-based applications. A broad range of integrative approaches are being applied in this system, including the application of state-of-the-art functional genetic assays, brain imaging, and genome sequencing. These advances position cavefish as a model organism for addressing fundamental questions about the genetics and evolution underlying the impressive trait diversity among individual populations within this species.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.330

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 head0.045
GPT teacher head0.241
Teacher spread0.196 · 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