Variabilité du chant de la paruline à gorge grise (Oporornis agilis)
Bibliographic record
Abstract
La paruline à gorge grise (Oporornis agilis) est un oiseau aux moeurs discrètes dont la situation des populations québécoises est préoccupante en raison de la perte croissante de son habitat, qui est convoité pour la culture du bleuet. L’objectif principal du projet dans lequel s’inscrit la présente recherche est de développer un outil de conservation non invasif permettant d’identifier individuellement les parulines à gorge grise au moyen de leur chant. L’objectif de cette recherche préliminaire est d’une part d’étudier la variabilité intra-individuelle du chant de l’espèce, afin de déterminer si ce dernier est suffisamment stable dans le temps et en présence d’un élément perturbateur (repasse de chants), et, d’autre part, d’évaluer si le chant est suffisamment différent d’un individu à l’autre pour permettre leur distinction. Les résultats révèlent que le chant de la paruline à gorge grise présente des variations temporelles et comportementales individuelles, mais que cette variabilité intra-individuelle (≤1% de la variance totale) n’est pas suffisante pour empêcher la distinction des individus (74 à 87% de la variance totale). La méthode d’identification vocale individuelle suggérée consiste à combiner l’analyse symbolique, une méthode novatrice pour l’analyse des vocalises aviaires, et l’analyse acoustique chant. \n \nThe Connecticut warbler (Oporornis agilis) is a bird with secretive habits whose population’s situation in Quebec populations is a cause of concern because of the increasing loss of its habitat, which is coveted for blueberry cultivation. The main objective of this research project is to develop a non-invasive conservation tool that can be used to identify individual Connecticut warbler through their song. The objective of this preliminary research is to study the intra-individual variability of the species' song, in order to determine whether the song is sufficiently stable over time and in the presence of a disturbing element (playback call of conspecific), and to evaluate whether the song is sufficiently different from one individual to another to allow their distinction. The results reveal that the song of the connecticut warbler presents individual temporal and behavioural variations, but that this intra-individual variability (≤1% of the total variance) is not sufficient to prevent the distinction of individuals (74 to 87% of the total variance). The suggested method for individual vocal identification is a combination of symbolic analysis, an innovative method for the analysis of avian vocalizations, and vocal acoustic analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".