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Record W7098373001

Shared processes in spatial rotation and music permutation

2001· article· en· W7098373001 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Studies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMental rotationPermutation (music)Object (grammar)Interval (graph theory)Test (biology)Task (project management)Rotation (mathematics)Musical
DOInot available

Abstract

fetched live from OpenAlex

An experiment was conducted in which subjects performed a three-dimensional spatial rota-tion test (24 trials) and a new test involving judgments of musical permutations (64 trials). Two types of musical permutations were used, including retrograde and inverse. In a retrograde permutation, the criterion melody was played backward in the test melody, and in an inverse permutation, an ascending or descending interval in the criterion melody became an opposite in the test melody. Subjects included 32 male and 64 female undergraduates at the University of Toronto. Regression analysis clearly showed that it was easiest to compare short retrograde permutations and that accuracy at discerning retrograde permutations predicted accuracy at judging spatial rotations. The implication is that a higher order ability to discriminate contour underlies both kinds of judgments. ª 2001 Academic Press Key Words: musical ability; spatial ability; sex differences; estrogen. General definitions of mental rotation ability refer to it as the act of imagining an object or pattern turning from one angular orientation to another (Corballis & McClaren, 1982; Linn & Peterson, 1985). In the original experiment on mental rota-tion (Shepard & Metzler, 1971), the task was to determine whether two-dimensional

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)0.002
metaresearch head score (Gemma)0.013
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.229
Teacher spread0.199 · 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

Citations0
Published2001
Admission routes1
Has abstractyes

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Same topicBotanical Studies and ApplicationsFrench-language works237,207