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        <identifier>oai:figshare.com:article/33219312</identifier>
        <datestamp>2026-09-21T01:34:44Z</datestamp>
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          <dc:title>Supporting data for “From a Small Brain Sees the Bigger Mind: A Cognitive Profile of Rosy-faced Lovebirds (&lt;i&gt;Agapornis roseicollis&lt;/i&gt;)”</dc:title>
          <dc:creator>Shengyu Wang (12989714)</dc:creator>
          <dc:creator>Simon Yung Wa Sin (15242371)</dc:creator>
          <dc:subject>Behavioural ecology</dc:subject>
          <dc:subject>avian cognition</dc:subject>
          <dc:subject>parrot intelligence</dc:subject>
          <dc:subject>Social Intelligence hypothesis</dc:subject>
          <dc:subject>rosy-faced lovebird</dc:subject>
          <dc:subject>social learning</dc:subject>
          <dc:subject>innovation</dc:subject>
          <dc:subject>personality</dc:subject>
          <dc:subject>memory</dc:subject>
          <dc:subject>associative learning</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;This dataset supports a PhD thesis investigating cognitive abilities in rosy-faced lovebirds and the evolutionary origins of advanced intelligence. The files are organized according to the data chapters of the thesis. Chapter 2 examines associative learning capacity and inference-based quantity discrimination in rosy-faced lovebirds, with all performance data recorded in a CSV file. Chapter 3 follows up on the associative learning study from Chapter 2, exploring how long memories persist, how they update in response to changing circumstances, and how updated memories are retained over time, all of which are also stored in a CSV file. The analyses in these chapters additionally incorporate bird personality data, provided in a separate supplementary CSV. Chapter 4 investigates how personality influences innovation and how birds recombine simple skills into complex integrated behaviours, with all performance metrics defined and stored in a CSV file. Chapter 5 focuses on lovebirds that failed in innovation tasks, examining how they use social learning and scaffolding to acquire complex skills; their performance data are also defined and stored in a CSV. The analysis for this chapter includes both innovation and personality data, which are kept in a separate CSV file. Each chapter folder contains an R Markdown (RMD) file that, when run with the accompanying CSV file(s), reproduces all statistical analyses and visualizations presented in that chapter. Collectively, these data and analytical scripts enable full replication of the studies and contribute to a deeper understanding of behavioural and cognitive adaptation, and more broadly, the evolution of advanced intelligence.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-21T01:34:44Z</dc:date>
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          <dc:identifier>10.25442/hku.33219312.v1</dc:identifier>
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          <dc:rights>CC BY-NC-ND 4.0</dc:rights>
          <dc:rights>Embargoed</dc:rights>
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