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Record W1914287955 · doi:10.1111/jfb.12191

Cephalic morphological variation in freshwater silversides <i>Odontesthes hatcheri</i> and <i>Odontesthes bonariensis</i> in Patagonia: introgression and ecological relationships

2013· article· en· W1914287955 on OpenAlexfundno aff
Sonia A. Crichigno, Cecilia Conte‐Grand, Miguel Ángel Battini, Víctor Cussac

Bibliographic record

VenueJournal of Fish Biology · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFish Biology and Ecology Studies
Canadian institutionsnot available
FundersOffice of International Science and EngineeringUniversidad Austral de ChileUniversidad de ConcepciónConsejo Nacional de Investigaciones Científicas y TécnicasFondo para la Investigación Científica y TecnológicaDalhousie UniversityBrigham Young UniversityNational Science Foundation
KeywordsBiologyIntrogressionMorphometricsZoologyEcomorphologyEcologyMeristicsHabitat

Abstract

fetched live from OpenAlex

Based on geometric morphometrics and discriminant analysis, the percentage of silverside Odontesthes hatcheri and Odontesthes bonariensis individuals identified by a taxonomic key and misclassified by discriminant analysis was obtained and a negative correlation between the percentage of misclassified individuals of O. hatcheri and the distance to the nearest hatchery stocking silversides was found, suggesting a genetic introgression. Morphological analyses between species, between populations and within populations pointed to the same anatomical structures, suggesting a nested variation related to environmental cues such as availability of littoral shelter. The dependence between the cephalic morphology of O. hatcheri and body size would be in agreement with the trophic niche shifts of the species. Introgression adds a new threat to the already observed decline of populations of O. hatcheri and suggests that this species deserves particular consideration in terms of conservation guidelines.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.370

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 integrity0.0000.001
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 head0.019
GPT teacher head0.207
Teacher spread0.188 · 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.

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

Citations15
Published2013
Admission routes1
Has abstractyes

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