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Record W2119418213 · doi:10.11646/zootaxa.1963.1.4

Three new pygmy seahorse species from Indonesia (Teleostei: Syngnathidae: Hippocampus)

2008· article· en· W2119418213 on OpenAlexaff
Sara A. Lourie, Rudie H. Kuiter

Bibliographic record

VenueZootaxa · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquatic life and conservation
Canadian institutionsMcGill University
Fundersnot available
KeywordsSeahorseBiologyTrunkAnatomyTeleosteiAppendageFish finHippocampusZoologyFish <Actinopterygii>FisheryEcologyNeuroscience

Abstract

fetched live from OpenAlex

Three new species of pygmy seahorse are described from Indonesia: Hippocampus pontohi and H. severnsi from Bunaken Island, off Sulawesi, and H. satomiae from Derawan Island, off Kalimantan. They are considered to be closely related to each other and to Hippocampus colemani. All three species are morphologically distinguished from the larger species of seahorses by the following combination of characters: 12 trunk rings, low number of tail rings (26–29), the placement of brooded young within the trunk region of males, and extremely small size (bargibanti, H. denise, H. colemani and H. minotaur) based on meristics, proportions, colour and body ornamentation. All three new species have a single gill opening as does H. colemani. Hippocampus pontohi and H. severnsi also share distinctive fleshy appendages with H. colemani but can be separated from the latter based on their body shape, raised angular coronet, larger orbit diameter, narrower trunk, fewer tail rings, smaller overall size and in the case of H. severnsi also colour. Diagnostic features of H. satomiae include 9 pectoral fin rays, 13 dorsal fin rays, spinous exterior, and distinct raised coronet with laterally expanded anterior and posterior flanges.

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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.043
GPT teacher head0.208
Teacher spread0.165 · 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

Citations35
Published2008
Admission routes1
Has abstractyes

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