Hook, line, and social media: crowd-sourced images reveal size and species patterns of ocean sunfishes (Tetraodontiformes, Molidae) from California to Alaska
Bibliographic record
Abstract
Taxonomic confusion and limited data have impeded species-level biogeographic analyses of the world’s largest bony fishes, ocean sunfishes (Molidae; ‘molids’), in many ecosystems. However, recent advances in molid taxonomy and the emergence of photo-based community-science platforms provide an opportunity to revisit species-level biogeography. In this study, we use crowd-sourced images of 1,213 ocean sunfishes to determine if molid morphology visible in citizen-science images permits reliable species determination. From the ensuing data, we describe patterns in molid size structure and species composition from 1,178 molids observed in the Alaska and California Current Systems (ACS and CCS, respectively). Molids <1 m total length (TL) were commonly reported in the CCS, particularly off the central coast of California, suggesting this area may function as a molid nursery. Molids >1 m TL were more commonly observed in both the CCS and cooler ACS, which suggests larger molids occupy a larger thermal range (ontogenetic habitat expansion) than smaller individuals. Overall, Mola mola was the most frequently observed species in both the ACS and CCS; however, the persistent occurrence of Mola tecta in both current systems suggests a range extension for this otherwise Southern Hemisphere species. The species identity of six M. tecta specimens from California and Alaska were verified with genetic analysis. Finally, two Mola alexandrini confirmed in the southern portion of the CCS represent the first records of this species in the Northeast Pacific Ocean.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".