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Record W2164396790 · doi:10.3161/000164510x551282

Note Types and Coding in Parid Vocalizations: The<i>chick-a-dee</i>Call of the Mexican Chickadee<i>Poecile sclateri</i>

2010· article· en· W2164396790 on OpenAlexaff
Michele K. Moscicki, Marisa Hoeschele, Christopher B. Sturdy

Bibliographic record

VenueActa Ornithologica · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiologyZoologyType (biology)CladeEcologyPhylogenetics

Abstract

fetched live from OpenAlex

To understand the communicative functions of any vocalization it is important to describe and classify the elements of that vocalization. Mexican Chickadees produce a namesake chick-a-dee call. Here, the note types (A, C, D, and Dh) from a sample of Mexican Chickadee chick-a-dee calls are identified, described, and classified. Frequency and temporal features of each note type are measured and compared to determine which features may be useful for note-type discrimination. Frequency measures, particularly peak frequency, appear to be most useful for discriminating among note types. Call syntax is analyzed to determine rules for note-type production. Mexican Chickadees produce the notes within their chick-a-dee calls in a consistent order: A → C → Dh → D with the potential for any note type to be repeated or omitted within this sequence. Similar to species in the brown-headed chickadee clade, B notes were not found in the calls of Mexican chickadees, suggesting this species may belong to the brown-headed clade. This work describes the chick-a-dee call of Mexican Chickadees and provides a foundation for future work aimed at understanding the communicative significance of this call within this species, as well as for comparative work on the chick-a-dee call among chickadee species.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.227

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.013
GPT teacher head0.267
Teacher spread0.254 · 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 designBench or experimental
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

Citations9
Published2010
Admission routes1
Has abstractyes

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