State–space model for light-based tracking of marine animals
Bibliographic record
Abstract
A coherent model is presented to estimate the most probable track of geographic positions directly from a series of light measurements. The model estimates two geographic positions per day, without reducing the daily light data to two threshold crossing times, its covariance structure is designed to handle high correlations due to for instance local weather conditions, and it can estimate the yearly pattern in latitudinal precision by propagating the data uncertainties through the geolocation process. The model is applied to one mooring study, one GPS drifter buoy study, and numerous simulated cases. The simulations are performed with realistic assumptions about the relationship between solar altitude and light and with realistic uncertainty parameters (all taken from real data). The simulations showed that all model parameters were identifiable, and that all tracks could be reconstructed within 1° or 2° latitude and 0.5° or 1° longitude. The mooring and drifter buoy data showed that the tracks could be reliably estimated, even in cases where the other methods had completely failed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".