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Record W2096100677 · doi:10.1071/zo13015

Pup numbers of the Australian sea lion (Neophoca cinerea) at The Pages Islands, South Australia, over two decades

2013· article· en· W2096100677 on OpenAlexaff
P. D. Shaughnessy, Simon Goldsworthy, P Burch, T. E. Dennis

Bibliographic record

VenueAustralian Journal of Zoology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsShaughnessy Hospital
FundersCommonwealth Scientific and Industrial Research Organisation
KeywordsBycatchFisheryPopulationGeographyEndangered speciesFishingBayThreatened speciesBiologyEcologyHabitatArchaeologyDemography

Abstract

fetched live from OpenAlex

The Australian sea lion is an Australian endemic, restricted to South Australia and Western Australia, with 86% of the population in South Australia. It was listed under the Commonwealth Environment Protection and Biodiversity Conservation Act as Vulnerable in February 2005, and the International Union for the Conservation of Nature has listed it as Endangered. Sea lions are taken as bycatch in the gill-net fishery for school shark and gummy shark, and the risk of extinction of breeding colonies is high even from low levels of bycatch. We assessed trends in pup population size at The Pages Islands, a large breeding colony in South Australia. Pup abundance was estimated by direct counting of live and dead pups; the maximum count in each breeding season was used for trend analysis. The average of direct counts of pups in 14 breeding seasons between 1989–90 and 2009–10 was 473 (s.d. = 58.4). There was no trend in pup numbers, contrasting with two other large colonies: Seal Bay, Kangaroo Island (decreasing), and Dangerous Reef (increasing since 2000). The Australian Sea Lion Management Strategy of the Australian Fisheries Management Authority aims to reduce sea lion bycatch in the shark fishery; a key item is a fishery closure around each breeding colony in South Australia. Implementation of the closure around The Pages should lower the risk of bycatch of its sea lions with foraging areas that previously overlapped with the fishery and should allow the colony’s population size to increase.

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)0.001
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 score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.029
GPT teacher head0.279
Teacher spread0.250 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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