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Record W7126244446 · doi:10.18280/ijdne.201209

Biomass and Population Structure of the Introduced Banggai Cardinalfish (Pterapogon kauderni) in Soropia Waters, Indonesia

2025· article· W7126244446 on OpenAlexvenueno aff
Subhan, Slamet Budi Prayitno, Aninditia Sabdaningsih, Asriyana, Ana Faricha

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2025
Typearticle
Language
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsnot available
FundersLembaga Pengelola Dana Pendidikan
KeywordsPopulation structureBiomass (ecology)PopulationBiodiversity

Abstract

fetched live from OpenAlex

The Banggai cardinalfish (Pterapogon kauderni) is an endemic species from the Banggai Islands, introduced to several regions in Indonesia, including Southeast Sulawesi, through the marine aquarium trade.P. kauderni inhabits shallow waters and associates with microhabitats such as sea urchins.This study aims to describe the population condition of the fish from a biomass perspective.The study included underwater visual censuses at 11 stationary points (SP) in three villages of Soropia District, Konawe Regency, Southeast Sulawesi Province, to collect data for estimating Pterapogon kauderni biomass.Furthermore, fish density estimation was conducted using the snowball sampling method to obtain an overview of the distribution and number of individuals at each observation location.The total biomass of P. kauderni was estimated at 16.47 kg/ha, lower than in its original habitat, Banggai Islands, Central Sulawesi, which is 18-32 kg/ha.The body length distribution influences biomass value.P. kauderni microhabitats included sea urchins and fire corals, found at depths of 4-7.5 m.The concentration of P. kauderni fish in this study was observed around anemones, fire corals, and branch corals, with the highest number of individuals found in the sea urchin microhabitat.P. kauderni can live peacefully in the same microhabitat as other fish.There was a strong positive correlation between sea urchin density and adult P. kauderni, with most of the observed P. kauderni fish using sea urchins for shelter.

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)0.000
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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.220
Teacher spread0.215 · 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

Citations0
Published2025
Admission routes1
Has abstractno

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