A volunteer-populated online database provides evidence for a geographic pattern in symptoms of black spot infections
Bibliographic record
Abstract
spp.). Photos were visually examined for symptomatic black spots indicative of infection by trematode species linked to black spot disease. Regardless of fish species group, symptoms of black spot pathogens were highly prevalent (27.1% of 314 fish) in watersheds of southern Ontario Canada, whereas mean prevalence was comparatively low elsewhere (7.8%). In one instance, a user uploaded a higher number of photos, with a higher percentage exhibiting signs of infection than other users in the watershed. However, it is difficult to tease apart if that user fished in waterbodies with high infection rates, uploaded more photos of symptomatic fishes, or some other explanation for the differences in user-reported fish with symptoms. Beyond this exception, geographic patterns in the frequency of black spot symptoms do not appear to be related to solely the users, suggesting the observed pattern is biological or ecological. While causative explanations remain conjectures, the data reported herein provides evidence that across four groups of fish, signs of black spot infections are more common in southern Ontario than other areas studied in North America. This work also represents an initial and unexpected utility of volunteer-population databases such as iNaturalist. Further data contributions could lead to better understanding of the causative agents to variation in black spot pathogens' occurrences.
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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".