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Record W1983703993 · doi:10.1037/a0016369

Individual differences in skilled reaching for food related to increased number of gestures: Evidence for goal and habit learning of skilled reaching.

2009· article· en· W1983703993 on OpenAlexafffund
Gita Gholamrezaei, Ian Q. Whishaw

Bibliographic record

VenueBehavioral Neuroscience · 2009
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyHabitPrimateGestureNeuroscienceDevelopmental psychologyCognitive psychologyPhysical medicine and rehabilitationSocial psychologyMedicine

Abstract

fetched live from OpenAlex

Skilled reaching in rodents and primate is motorically similar, but success in reaching by rodents is distinctively variable. The source of this variability has not been examined previously. Long-Evans rats were videotaped as they reached for food in 2 different reaching tasks, and endpoint measures of performance were examined in relation to variables previously associated with individual differences, including testing procedures, rehabilitation, movement ability, general locomotor activity, and cortical anatomy. There were individual differences in performance, but these were not related to the dependent measures related to training, movement ability, locomotor activity, or anatomy (e.g., brain with cortical thickness, acetylcholinesterase and neuron density, pyramidal tract size). Success was negatively related to numbers of gestures (non-weight-bearing movements of the reaching limb) used on a reach, however. The results are discussed in relation to the idea that individual differences in response strategy bias some rats to use a more successful goal strategy and others to use a less successful habit strategy for skilled reaching.

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)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.888
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.094
GPT teacher head0.353
Teacher spread0.259 · 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

Citations18
Published2009
Admission routes2
Has abstractyes

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