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Record W2170981046 · doi:10.1111/jfb.12707

<scp>DNA</scp> barcoding and morphological identification of neotropical ichthyoplankton from the Upper Paraná and São Francisco

2015· article· en· W2170981046 on OpenAlexaff
R. A. Becker, Naiara Guimarães Sales, G. M. Santos, Gilmar Bastos Santos, Daniel C. Carvalho

Bibliographic record

VenueJournal of Fish Biology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsUniversity of Toronto
FundersCompanhia Energética de Minas GeraisFundação de Amparo à Pesquisa do Estado de Minas Gerais
KeywordsDNA barcodingBiologyIchthyoplanktonIdentification (biology)Taxonomy (biology)HydrographyBiodiversityZoologyLarvaFish <Actinopterygii>Fish larvaeFisheryEcologyGeographyCartography

Abstract

fetched live from OpenAlex

The identification of fish larvae from two neotropical hydrographic basins using traditional morphological taxonomy and DNA barcoding revealed no conflicting results between the morphological and barcode identification of larvae. A lower rate (25%) of correct morphological identification of eggs as belonging to migratory or non-migratory species was achieved. Accurate identification of ichthyoplankton by DNA barcoding is an important tool for fish reproductive behaviour studies, correct estimation of biodiversity by detecting eggs from rare species, as well as defining environmental and management strategies for fish conservation in the neotropics.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score0.501

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.277
Teacher spread0.248 · 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 designObservational
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

Citations68
Published2015
Admission routes1
Has abstractyes

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