Seasonal shoreline change in northeastern Haida Gwaii dataset
Bibliographic record
Abstract
This dataset comprises 32 manually digitized shoreline shapefiles representing the coastline near Masset, in northeastern Haida Gwaii, British Columbia. It also includes an onshore baseline and a series of transects spaced at 30 m intervals extending seaward from the baseline. These data were used to analyze shoreline position changes using the U.S. Geological Survey's Digital Shoreline Analysis System (DSAS). This dataset was used to investigate shoreline change between Masset and the Sangan River over a 15-year period from 2007 to 2022. Shorelines were digitized twice annually, in April and October, to capture the end of winter and summer conditions, respectively. These seasonal envelopes allowed for investigations into maximum rates of erosion and aggradation. The seasonal shorelines were digitized using Landsat 7 and 8 panchromatic imagery, where the water-land interface was used as the shoreline proxy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.011 |
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".