Quantification of marine macro-debris abundance around Vancouver Island, Canada, based on archived aerial photographs processed by projective transformation
Bibliographic record
Abstract
The abundance of marine macro-debris was quantified with high spatial resolution by applying an image processing technique to archived shoreline aerial photographs taken over Vancouver Island, Canada. The photographs taken from an airplane at oblique angles were processed by projective transformation for georeferencing, where five reference points were defined by comparing aerial photographs with satellite images of Google Earth. Thereafter, pixels of marine debris were extracted based on their color differences from the background beaches. The debris abundance can be evaluated by the ratio of an area covered by marine debris to that of the beach (percent cover). The horizontal distribution of percent cover of marine debris was successfully computed from 167 aerial photographs and was significantly related to offshore Ekman flows and winds (leeway drift and Stokes drift). Therefore, the estimated percent cover is useful information to determine priority sites for mitigating adverse impacts across broad areas.
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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) | 0.002 | 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".