MétaCan
Menu
Back to cohort
Record W3016359035 · doi:10.1093/jmammal/gyaa028

Growth and development of North Pacific gray whales (Eschrichtius robustus)

2020· article· en· W3016359035 on OpenAlexaff
Selina Agbayani, Sarah M. E. Fortune, Andrew W. Trites

Bibliographic record

VenueJournal of Mammalogy · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
Fundersnot available
KeywordsAllometryLife expectancyGray (unit)BiologyGompertz functionGrowth modelDemographyAnimal scienceGeographyEcologyMathematicsStatisticsPopulationMedicine

Abstract

fetched live from OpenAlex

Abstract Understanding variability in growth patterns of marine mammals provides insights into the health of individuals and status of populations. Body growth of gray whales (Eschrichtius robustus) has been described for particular life stages, but has not been quantified across all ages. We derived a comprehensive growth equation for gray whales by fitting a two-phased growth model to age-specific length data of eastern North Pacific gray whales that were captured, stranded, or harvested between 1926 and 1997. To predict mass-at-age, we used the allometric relationship between mass and length. We found that on average (± SD), calves were 4.6 ± 0.043 m and 972 ± 26 kg at birth, and reached 8.5 ± 0.095 m and 6,019 ± 196 kg by the end of their first year of life (n = 118). Thus, calves almost double (2×) in length and octuple (8×) in mass while nursing, and are effectively about two-thirds of their asymptotic adult length and one-third of their maximum mass when weaned. The large sample of aged individuals (n = 730) indicates that gray whales live up to ~48 years and have a life expectancy of < 30 years. Adult females attain a mean (± SD) asymptotic size of 13.1 ± 0.048 m and 20,758 ± 222 kg, while the smaller males average 12.6 ± 0.048 m and 19,938 ± 222 kg at ~40 years of age. Females are thereby ~4% longer and heavier than males. These age-specific estimates of body size can be used to estimate food requirements and assess nutritional status of individuals.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.364

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.209
Teacher spread0.186 · 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.

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

Citations26
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of MammalogySame topicMarine animal studies overviewFrench-language works237,207