Biotic exchange from movement of ‘static’ maritime structures
Bibliographic record
Abstract
Coastal infrastructure provides extensive habitat for marine nonindigenous species (“NIS”), especially biofouling species. Ecosystem transplants can arise when static maritime structures (“SMS”) are relocated under slow towing speeds following long periods of biofouling accumulation. Translocations of SMS occur more often than acknowledged and represent a high-risk vector of marine NIS that is largely overlooked and unregulated. We compiled geolocations and movement patterns for oil platforms, derelict/obsolete vessels, barges, dry docks, floating lodges, homes and docks, aquaculture gear and buoys for the NE Pacific coast. We related these data to NIS richness within the region and to global examples of SMS movement. Our review and synthesis of SMS, paired with biofouling surveys before and after dock towing events, reveal the growing NIS vector opportunities resulting from sprawling coastal infrastructure. As coastal development continues apace in the Anthropocene, this emerging management challenge will require strong frameworks and workable solutions for a global issue that currently lacks incentives to prevent species transfers and invasions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".