Marcaccio and Chow-Fraser 2018 Final report to MTO
Bibliographic record
Abstract
We mapped the distribution of invasive Phragmites australis (European common reed) in MTO-operated roadways of southern Ontario using airphotos from a provincial database, the Southwestern Ontario Orthophotography Project (SWOOP), which covers all highways from Windsor east to Norfolk/Niagara and north to Tobermory. We mapped all available SWOOP images acquired in 2006, 2010 and 2015. In addition, we delineated invasive Phragmites along MTO-operated roadways within the footprint of the Southcentral Ontario Orthphotography Project (SCOOP acquired in 2013) and the Central Ontario Orthophotography Project (COOP acquired in 2016); the mapping excludes the Greater Toronto Area but includes Prince Edward county, roads through the city of Barrie, and north to Parry Sound. Based on available orthophotos for SWOOP only, total areal cover of invasive Phragmites expanded an order of magnitude between 2006 and 2010 (26.8 to 259.7 ha, respectively); between 2010 and 2015, there was only an increase of 7.2% (278.4 ha), presumably because of ongoing herbicide treatments that began on selected roads beginning in 2012. Expansion rate differed between road types, with 400-series highways having significantly greater expansion rates than non-400 highways (24.5 vs 6 times, respectively). Areas covered by SCOOP images had an areal cover of 152 ha in 2013, while that for COOP images had an areal cover of 7.8 ha in 2016. This inventory is freely available for anyone to update using provincial orthophotos or medium to high- resolution satellite imagery such as Sentinel 2.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.093 | 0.035 |
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".