An overview of fungal taxonomic, functional, and genetic diversity in coastal and oceanic biomes in megadiverse Mexico
Bibliographic record
Abstract
Abstract A comprehensive literature review of mycodiversity in sandy beaches and oceanic environments in Mexico is presented through the analysis of published works from 1949 to early 2023. In addition, four unexplored sandy beaches in the Pacific Ocean and Gulf of California were sampled in order to fill knowledge gaps in terms of sampling biases. Marine fungi of Mexico were reported from water column, sediment, and debris samples collected in sandy beaches, open ocean, deep-sea plains, hydrothermal vents, and oxygen minimum zones in the Gulf of Mexico, the Pacific Ocean, the Gulf of California, and the Caribbean Sea. The taxonomic, functional, and genetic diversity, as well as distribution patterns and potential use of marine fungal genetic resources are discussed. A list of 126 species in 83 genera, 40 families, 25 orders, 12 classes, three phyla and one subphylum (excluding non-cultured taxa) of marine fungi is documented from Mexico. Lastly, we identified areas that would benefit from additional research, including the exploration of further deep-sea biomes in the Pacific Ocean, and coastal areas covering ecoregions in the states of Sonora, Sinaloa, Nayarit, Michoacán, and Oaxaca.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".