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Record W4313419776 · doi:10.14430/arctic76337

Ladoga Ringed Seal (Pusa hispida ladogensis) Can Breed on Land: A Case Study of the Nursing Period

2022· article· en· W4313419776 on OpenAlexvenueno aff
Anna Loseva, Olga Chirkova, Evgeniy Akhatov

Bibliographic record

VenueARCTIC · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
Fundersnot available
KeywordsPredationWeaningArcticPusaBreedBiologyPredatorFisheryEcologyAnimal scienceAgronomy

Abstract

fetched live from OpenAlex

The ringed seal gives birth and nurses offspring in a subnivean lair in fast ice. Its breeding habitat is transforming under the impact of climate change. Here we report the outcome of an observation of a female freshwater Ladoga ringed seal (Pusa hispida ladogensis) and her pup during the 2020 breeding season, when less than 1% of Lake Ladoga was covered with ice. We located a newborn pup in a coastal zone of an island and tracked its survival on land using the camera trap method during daylight. Altogether, we captured 2978 photos, in which the seals were present in 637. The female nursed the pup at the birth site for 34 – 37 days, which is similar to the lactation period in lairs of the Arctic subspecies (36 – 41 days, 39 days on average). The female either stayed with the pup or spent time in prolonged aquatic bouts during the day. Percentage of suckling was in the range of 2.4% – 4.7% (mean 3.3%, SD = 1.1) on different days. Based on an additional video recording, we found that the pup’s behaviour was characterized by a high level of vigilance in comparison with openly breeding phocid seals. This case study indicates that the ringed seal in Lake Ladoga is able to nurse pups on land from soon after birth to pre-weaning. However, breeding success in warm springs can be constrained by predator pressure.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.023
GPT teacher head0.244
Teacher spread0.222 · 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 teacher head, not a consensus.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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