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Record W4313421831 · doi:10.1080/21594937.2022.2152535

Self-handicapping in object play: how belugas (<i>Delphinapterus leucas</i>) make play difficult

2022· article· en· W4313421831 on OpenAlexaff
Jackson R. Ham, Malin K. Lilley, Malin R. Miller, Jean‐Baptiste Leca, Sergio M. Pellis, Heather M. Hill

Bibliographic record

VenueInternational Journal of Play · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsBeluga WhaleBelugaLeucasObject (grammar)PsychologyBiologyEcologyFisheryComputer science

Abstract

fetched live from OpenAlex

Although observed in animals from various taxa, object play is not well studied. While studying object play in managed care belugas (Delphinapterus leucas), we noticed that, in some cases, the belugas self-handicap their play. For example, a beluga may push a ball onto a ledge, so that the object can only be reached by the beluga beaching itself. Self-handicapping has been described in locomotor and social play, but is rarely, if ever, reported in object play. The belugas of this study self-handicap themselves while playing with objects in 3.9% of cases. All nine of the immature belugas were observed to self-handicap, which accounted for 90.6% of the self-handicapping bouts observed. Even though rare, some degree of self-handicapping may be important in ensuring continued playfulness irrespective of the type of play involved. Broader comparative studies on the presence and role of self-handicapping across species and types of play are needed.

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 score0.023
Threshold uncertainty score0.045

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 studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.013
GPT teacher head0.241
Teacher spread0.228 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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