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Record W1998188630 · doi:10.1037/0735-7036.120.3.184

When do octopuses play? Effects of repeated testing, object type, age, and food deprivation on object play in Octopus vulgaris.

2006· article· en· W1998188630 on OpenAlexaff
Michael J. Kuba, Ruth A. Byrne, Daniela V. Meisel, Jennifer A. Mather

Bibliographic record

VenueJournal of comparative psychology · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCephalopods and Marine Biology
Canadian institutionsUniversity of Lethbridge
FundersKonrad Lorenz Institute for Evolution and Cognition Research
Keywordsoctopus (software)HabituationTraitCognitionObject (grammar)PsychologyDevelopmental psychologyBiologyZoologyEvolutionary biologyCognitive psychologyEcologyNeuroscienceArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Studying play behavior in octopuses is an important step toward understanding the phylogenetic origins and function of play as well as the cognitive abilities of invertebrates. Fourteen Octopus vulgaris (7 subadults and 7 adults) were presented 2 Lego objects and 2 different food items on 7 consecutive days under 2 different levels of food deprivation. Nine subjects showed play-like behavior with the Lego objects. There was no significant difference in play-like behavior corresponding to food deprivation, age, and sex of the octopuses. The sequence of behaviors, from exploration to play-like behavior, had a significant influence on the establishment of play-like behavior, as it occurred mostly on Days 3-6 of the 7-day experiment. The pattern of development of play-like activities after a period of exploration and habituation in this study agrees with the hypothesis that object play follows object exploration. A homologous origin of this behavioral trait in vertebrates and invertebrates is highly unlikely, as the last common ancestor might not have had the cognitive capacity to possess this trait.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.041
GPT teacher head0.306
Teacher spread0.265 · 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

Citations154
Published2006
Admission routes1
Has abstractyes

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