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Record W4389396863 · doi:10.1038/s41598-023-48684-3

Apparent coordinated and communal hunting behaviours by Erabu sea krait Laticauda semifactiata

2023· article· en· W4389396863 on OpenAlexaff
Ruchira Somaweera, Vinay Udyawer, A.A. Thasun Amarasinghe, Joe de Fresnes, Jay Catherall, G. N. Molchanova

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsForagingPredationEcologyHabitatGeographyBiologyInterspecific competitionFishery

Abstract

fetched live from OpenAlex

Opportunistic observations of Erabu sea kraits (Laticauda semifaciata) provide evidence that this species undertake a novel foraging tactic; coordinated communal hunting. Erabu sea kraits prey on cryptic fish species in highly complex reef habitats. Intra- and interspecific cooperative hunting strategies may increase chances for all members of the hunting party to encounter and capture prey in these complex habitats. Here, we observed 52 instances of communal hunting by Erabu sea kraits with conspecifics and other predatory fishes at recreational dive sites in Southern Lombok, Indonesia. These observations highlight the potential higher cognitive capacity of sea kraits to coordinate activities around communal hunting events.

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 score0.011
Threshold uncertainty score0.021

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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