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Record W4313027521 · doi:10.1007/978-3-031-06153-0_23

Cetaceans of São Tomé and Príncipe

2022· book-chapter· en· W4313027521 on OpenAlexfundno aff
Inês Carvalho, Andreia Pereira, Francisco Martinho, Nina Vieira, Cristina Brito, Marcio Bulgarelli Guedes, Bastien Loloum

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaFonds Français pour l'Environnement MondialFederation for the Humanities and Social SciencesWildlife Conservation Society
KeywordsWhalingArchipelagoFisherySperm whaleWhaleGeographyPelagic zoneApex predatorBiodiversityBottlenose dolphinBaleenHabitatOceanographyEcologyBiologyGeology

Abstract

fetched live from OpenAlex

Abstract The Gulf of Guinea is a marine biodiversity hotspot, but cetacean fauna in these waters is poorly studied and our knowledge is documented mostly from opportunistic (sightings and strandings) and whaling data. This chapter presents a short review of historical whaling in the Gulf of Guinea and an update of cetacean biodiversity in the waters of São Tomé and Príncipe. Observations since 2002 have confirmed the presence of 12 species of cetaceans, 5 of them new to the region (Striped Dolphin, Rough-toothed Dolphin, Risso’s Dolphin, Pygmy Killer Whale, and Dwarf Sperm Whale). The archipelago seems to be an important area for cetaceans, with some species (Bottlenose Dolphin and Pantropical Spotted Dolphin) being present throughout the year. The volcanic origin of the archipelago produces great depths very close to the coast, which may favor the approach of pelagic species like Sperm Whales, Killer Whales, and Short-finned Pilot Whales. Bays and shallow waters may also serve as protection or rest areas for particular groups, like mother and calf pairs of Humpback Whales. Major anthropogenic threats to cetaceans in São Tomé and Príncipe include habitat degradation due to overfishing, fisheries interactions, possibly some occasionally directed takes and, more recently, oil and gas prospecting. Consistent and dedicated research to inform national legislation, together with increasing environmental awareness and local engagement, would help to identify effective cetacean conservation strategies in the archipelago.

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: Review · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.208
Teacher spread0.190 · 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
GenreReview

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

Citations5
Published2022
Admission routes1
Has abstractyes

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