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Record W6948494869 · doi:10.5061/dryad.gmsbcc2mw

Links between personality traits and problem-solving performance in zebra finches (Taeniopygia guttata)

2022· dataset· en· W6948494869 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typedataset
Languageen
FieldMedicine
TopicBiological and pharmacological studies of plants
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHyporeflexiaNucleofectionCircumstantial evidenceArticular cartilage damageGestational periodTubulopathy

Abstract

fetched live from OpenAlex

Consistent individual differences in behaviour across time or contexts (i.e., personality types) have been found in many species and have implications for fitness. Likewise, individual variation in cognitive abilities has been shown to impact fitness. Cognition and personality are complex, multidimensional traits. However, previous work has generally examined the connection between a single personality trait and a single cognitive ability, yielding equivocal results. Links between personality and cognitive ability suggest that behavioural traits coevolved and highlight their nuanced connections. Here we examined individuals’ performance on multiple personality tests and repeated problem-solving tests (each measuring innovative performance). We assessed behavioural traits (dominance, boldness, activity, risk-taking, aggressiveness, and obstinacy) in 41 captive zebra finches. Birds’ scores for boldness and obstinacy were consistent over two years. We also examined whether personality correlated with problem-solving performance on repeated tests. Our results indicate that neophobia, dominance, and obstinacy were related to successful solving, and less dominant, more obstinate birds solved the tasks quicker on average. Our results indicate the importance of examining multiple measures over a long period. Future work that identifies links between personality and innovation in non-model organisms may elucidate the coevolution of these two forms of individual differences.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0760.000

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 head0.074
GPT teacher head0.288
Teacher spread0.214 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicBiological and pharmacological studies of plantsFrench-language works237,207