LIDAR Technology Applied in Coastal Studies and Management
Bibliographic record
Abstract
The FUDOTERAM is a national Canadian light detection and ranging (LIDAR) project founded by the Canadian Network of Excellence GEOmatics for Informed DEcision (GEOIDE) that investigates data fusion from airborne, marine, and terrestrial mapping sensors. In March 2009, the second Fusion des Données TERrestres, Aériennes et Marines (FUDOTERAM) workshop was held in Quebec City, Quebec, Canada. The focus of the workshop was on international collaboration: Workshops can provide an international platform for sharing ideas and study results among academy, industry, mapping and charting organizations, and service providers. LIDAR work and research included data collected from seven different coastal areas in four nations. This special issue contains selected studies from the second FUDOTERAM workshop on LIDAR technology applied in coastal studies and management. Current studies in this special issue explore LIDAR processing in charting and mapping organizations, shoreline mapping, data integration, coastal processes and coastal management, and seafloor characterization.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".