Ascophyllum nodosum Le Jolis Harvesting Impacts and Management Options Using GPS Tracking of Mechanical Harvesters in Nova Scotia, Canada
Bibliographic record
Abstract
Abstract Area based management of Ascophyllum nodosum Le Joli in the Canadian Maritimes has advanced over the past 60 years from open buying stations in Bays to quota-based area management under coastal leases. In 1989 the resource was divided into geographical sectors containing .9 to 17.6 ha containing 92 t to 2105 t of harvestable biomass. Sectors are the units of management plans under guidelines of the provincial government. GPS tracking mechanical harvesting to Nova Scotia began in 2017 using a new mechanical harvester in a pilot harvest. GPS tracking allowed the calculation of yield with the time, distance, and cutting swath. Harvests were conducted within target bed polygons of 200 m− 2 to 1280 m− 2. Production per hour averaged 1135 ± 169 kg h− 1 yielding 5.96 ± 1.01 kg m− 2 of swept track. The average exploitation rate within targeted polygons was 33.1 ± 14.5%. This level of geographic resolution of the harvest permits significant improvements in management practices, control of management plans, pre and post assessments of the resource. It is a method of addressing landscape scale questions relating to harvesting impacts.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.001 | 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".