MétaCan
Menu
Back to cohort
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 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.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.029
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