Preliminary results on automated video-imaging for the study of behavioural rhythms of tubeworms from the tempo-mini ecological module (neptune, canada)
Bibliographic record
Abstract
The presence of behavioural rhythms has been studied in organisms of coastal areas in relation to circadian and tidal cycles, but their presence in benthic fauna inhabiting dark deep-sea regions remains largely unknown. Cabled video-observatories allow the study of these activity rhythms via the acquisition of pictures or footages over extended periods of time. In this work, we present the preliminary steps in the automation of biological data extraction for the determination of deep-sea fauna activity rhythms with TEMPO-mini (NEPTUNE; Canada). Automated analyses of tube worm behaviour were carried out with the Hough transform algorithm. Some different testing parameters were applied to the same image with siboglinid tubes. Tube openings identifications showed to be difficult, since circle placing was in some cases attributed to animals. The future step of automation will be to run the Hough transform algorithm within sub Region of Interests were tube identifications is the most efficient as we identified with this preliminary screening. Then, we will focus on each singe individual producing time series in terms of opening identification (as marker of moments of animals’ retractions) per unit of time (e.g. 10 min).
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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 | 0.000 | 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) | 0.000 | 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".