Gene transcription patterns in response to low level petroleum contaminants in Mytilus trossulus from field sites and harbors in southcentral Alaska
Bibliographic record
Abstract
The 1989 Exxon Valdez oil spill damaged a wide range of natural resources, including intertidal communities, and post-spill studies demonstrated acute and chronic exposure and injury to an array of species. Standard toxicological methods to evaluate petroleum contaminants have assessed tissue burdens, with fewer assays providing indicators of health or physiology, particularly when contaminant levels are low and chronic. Marine mussels are a ubiquitous and crucial component of the nearshore environment, and new genomic technologies exist to quantify molecular responses of individual mussels to stimuli, including exposure to polycyclic aromatic hydrocarbons (PAHs). We used gene-based assays of exposure and physiological function to assess chronic oil contamination using the Pacific blue mussel, Mytilus trossulus. We developed a diagnostic gene transcription panel to investigate exposure to PAHs and other contaminants and its effects on mussel physiology and health. During 2012–2015, we analyzed mussels from five field sites in western Prince William Sound, Alaska, with varying oil histories from the 1989 Exxon Valdez oil spill, and from three boat harbors in the area. Gene transcription patterns of mussels from harbors were consistent with elevated exposure to PAHs or other contaminants, whereas transcription patterns of mussels sampled from shorelines in areas affected by the oil spill indicated no PAH exposure.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".