Sentinels of Change Sea surface temperature time series data along the British Columbia Coast
Bibliographic record
Abstract
This dataset is comprised of sea surface temperature data collected using HOBO TidbiT MX Temperature 400 data loggers (MX2203) deployed in various locations across the BC coast but particularly in the Canadian portion of the Salish Sea. Loggers are suspended at 0.5 metres depth from floating docks in proximity to light traps as part of the Sentinels of Change project which monitors larval Dungeness crab (Metacarcinus magister) using light traps. The loggers are programmed to record the water temperature at 10 minute intervals, starting at 12:00 on April 15th until 12:00 September 1st, each year, starting in 2022. Loggers are removed from the water after September 1st and replaced the following spring before April 15th. These data will be collected each year until 2030. This data package includes: -Sea surface temperature data from April 15th to September 1st for 2022, 2023, and 2024 (the duration of the light trap collection season) -Site metadata, including temperature logger location
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.015 |
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".