Taking the Pulse of Changing Phenologies and Biodiversity: The Acoustic Way
Bibliographic record
Abstract
Photo 1. A sample of Arctic species whose calls and songs were annotated in the ArcticBirdSounds database. (A) Two common ravens (Corvux corax—CORA in the dataset) vocalizing while flying. (B) Lapland longspur (Calcarius lapponicus—LALO), one of the most frequent species seen singing in the study sites. (C) Black-bellied plover (Pluvialis squatarola—BBPL) alerting with a closed beak near its nest. (D) Semipalmated sandpiper (Calidris pusilla—SESA) alerting while displaying a rhynchokinesis, a feature made possible thanks to the elasticity in both upper and lower tips of the bill. (E) Baird's sandpiper (Calidris bairdii—BASA) calling during breeding. (F) A vocalizing pair of snow geese (Chen caerulescens—SNGO) attacking an intruder in their territory. (G) A female red phalarope (Phalaropus fulicarius—REPH) calling during a foraging bout in an arctic pond. (H) Long-tailed jaeger (Stercorarius longicaudus—LTJA) calling its partner. Photo credit: Nicolas Lecomte (A–C; E–G); Sylvain Christin (D). Photo 2. Examples of typical high arctic landscapes where the acoustics recorders were set from early spring (top picture) to the end of the breeding summer (middle image). The bottom left image shows the acoustic recorder before setting it in its protective casing (bottom middle image). The bottom left image illustrates a simple and concealed placement of a recorder pointed by the white arrow. Photo credit: Nicolas Lecomte and Sylvain Christin (bottom right image only). Photo 3. Example of an annotated arctic chorus with calls and songs of four different tundra species: (a) the lapland longspur (Calcarius lapponicus—LALO in the dataset), (b) the ruddy turnstone (Arenaria interpres—RUTU), (c) the pectoral sandpiper (Calidris melanotos—PESA), and (d) the dunlin (Calidris alpina—DUNL). This summary figure of separate and overlapping acoustic signals is called a spectrogramm and captures time (0.1 seconds, s) in the x-axis, sound frequencies (in Khz) in the y-axis, and intensity (in dB) in a color scheme. The cloud of points close to the minimum frequency are typical of outdoor recordings that usually capture ambient noise. Photo credit: Nicolas Lecomte. These photographs illustrate the article “ArcticBirdSounds: An open-access, multiyear, and detailed annotated dataset of bird songs and calls” by Sylvain Christin, Christine Chicoine, Tommy O'Neill Sanger, Mélanie F. Guigueno, Jannik Hansen, Richard B. Lanctot, Douglas MacNearney, Jennie Rausch, Sarah T. Saalfeld, Niels M. Schmidt, Paul A. Smith, Paul F. Woodard, Éric Hervet, and Nicolas Lecomte published in Ecology. https://doi.org/10.1002/ecy.4047
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".