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Record W4409132004 · doi:10.1177/03057356251322077

Absolute pitch shift

2025· article· en· W4409132004 on OpenAlexaff
Jon Baggaley

Bibliographic record

VenuePsychology of Music · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsAthabasca University
Fundersnot available
KeywordsPsychologyAbsolute (philosophy)Absolute pitchAudiologyTheologyPerceptionMedicineNeurosciencePhilosophy

Abstract

fetched live from OpenAlex

Absolute pitch (AP) enables its possessors to identify musical notes and keys by qualities of tone height and tone chroma. With advancing age, an unknown proportion of AP possessors perceives changes in these qualities, usually described as in the sharp direction and to the extent of a semitone or tone. The phenomenon is identified here as absolute pitch shift (APS). Using a cellphone-based tone generator, the writer conducted an N = 1 examination of the APS in his central musical range. The shift was greater at the centre of the range than at its extremes, causing him to perceive incoming tones as 1 to 4 semitones sharper than his recall of them in the A = 440 cps (concert pitch range). The report focusses on the comparative flatness of his AP memories of the tones, expressed with greater precision in cycles per second than by the names commonly given to their physical versions. The altered pitch perceptions are considered due to changes at the basilar membrane level in older individuals, and are labelled here as basilar AP. The internal pitch template’s role in memorising tone frequencies in the inner ear is labelled cortical AP. Implications are considered for further studies of AP and APS latency.

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)0.003
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 score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.005

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 head0.066
GPT teacher head0.361
Teacher spread0.295 · 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
Published2025
Admission routes1
Has abstractyes

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