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Record W2771474708

Singing and Song: A Biophysical and Evolutionary Perspective

2017· article· en· W2771474708 on OpenAlexaff
Dianne Cameron

Bibliographic record

VenueThe Journal of Macrodynamic Analysis (Memorial University of Newfoundland) · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsLaurentian University
Fundersnot available
KeywordsSingingNatural (archaeology)SoundscapeCommunicationMeaning (existential)BiologyAnimal communicationEcologyPsychologySound (geography)Acoustics
DOInot available

Abstract

fetched live from OpenAlex

The periodicity of natural signals from our environment since the dawn of life on earth has provided the foundation for development of rhythmic responses innate to living organisms, ranging from ancient bacteria to modern humans. The evolution of organs tuned to auditory signals – especially since the colonization of terrestrial environments by early vertebrates – has been matched by the coevolution of vocalization from the production of simple warnings and alarms to complex patterns communicating sophisticated messages. The need to interpret and produce auditory information is essential for a diverse spectrum of animals. At what point does complex vocalization become “song”, and what is it that we regard as “singing”?We recognize “songs” and “singing” in the spring chorus of amphibians, the humming and chirping of insects, the species-specific songs of birds, and the complex communication of humpback whales and other cetaceans. These terms vary in meaning when describing such vocalizations compared to humans. For human singers, the act of singing and the meaning of song have strong emotional and physical components that are profound and personal, with demonstrated effects on brain activity and development, health and well-being. Is this uniquely human?This paper reviews the biophysics of hearing and the concept of singing from the perspective of evolution within the natural rhythmic soundscape of our world.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.006
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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 designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

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