Statistical classification of odontocete clicks
Why this work is in the frame
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Bibliographic record
Abstract
To the best of our knowledge, all odontocetes produce some kind of click like vocalisation, which is used primarily for echolocation but may also play a role in social communication.Characteristics of these echolocation pulses range from the broad band but relatively low frequency clicks of sperm whales to the ultrasonic, narrow-band clicks of harbour porpoise.Although these clicks are often easily detected, it can be difficult to classify them to species, thereby hampering efforts to monitor and study odontocetes using passive acoustics.Candidate clicks from three species were detected using a simple energy trigger, operating in the frequency band of interest.The clicks were then identified to species using two different statistical classifiers to separate beaked whale vocalisations from those of other odontocete sounds.In the first, a number of parameters (peak frequency, mean frequency, sweep frequency, click duration, width of principal spectral peak and the relative energy in different frequency bands) were calculated and a tree classifier was used to separate clicks of different species.In the second, the spectral energy in 32 relatively coarse energy bands 1.5 kHz wide were used as input to a multivariate classifier.Both classifiers were trained and tested using data provided to the 3rd International Workshop on Detection and Classification of Marine Mammals using Passive Acoustics in order to assess the classifiers performance with Blainville's beaked whales, short-finned pilot whales and Risso's dolphin clicks.The methods were also applied to survey data collected using a towed hydrophone deployed from a sailing research vessel in the Bahamas.Some of the towed hydrophone data were collected over the US Navy's AUTEC range where independent confirmation of beaked whale vocal activity was available from bottom-mounted hydrophones. s o m m a i r eL 'tat actuel de nos connaissances nous permet d'affirmer que tous les odontocetes mettent des sons de type impulsifs, aussi appels clics, destins surtout l 'cholocation, mais ils peuvent galement tre utiliss pour la communication.En fonction des espces, ces clics peuvent couvrir une bande de frquence plus ou moins large.Le cachalot produit des clics couvrant une large bande de basses frquences, alors que chez le marsouin, l 'cholocation est caractrise par des clics ultrasoniques couvrant une bande de frquence troite.En slectionnant les clics ayant une puissance suprieure un certain seuil avec un simple dtecteur d 'nergie dans la bande de frquence qui nous intressait, nous avons collect les clics de 3 espces (Baleine bec de Blainville, globicphale tropical et dauphin de Risso).Deux mthodes d 'analyse nous ont permis de discriminer les sons de la baleine bec de Blainville de ceux des 2 autres espces.Pour la premire mthode, diffrent paramtres (pic de frquence, frquence moyenne, variation de frquence, dure du signal, largeur du spectrogramme et nergie relative dans les diffrentes bandes de frquences) ont t extraits de chaque clic et utiliss dans un arbre de classification afin de sparer les espces.Pour la seconde mthode, l'nergie contenue dans 32 bandes de 1.5kHz a servi de donnes pour une analyse multivarie.Les 2 classificateurs ont t entrains et tests en utilisant les donnes de la 3ime commission internationale de dtection et de classification des mammifres marins en utilisant l 'acoustique passive.L 'objectif tait de mesurer la performance des classificateurs pour discriminer la baleine bec de Blainvilles, le globicphale tropical et le dauphin de Risso.Ces 2 mthodes ont ensuite t appliques sur des donnes collectes au Bahamas partir d 'hydrophones tirs par un voilier de recherche.Quelques donnes furent collectes au dessus de la zone du rseau d 'hydrophone Autec, appartenant la marine Amricaine, permettant d 'obtenir une confirmation indpendante de l'activit sonore des baleines bec via ce rseau sous-marin.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it