Bias-corrected NA-CORDEX projections for Trail Valley Creek, NWT, Canada
Bibliographic record
Abstract
This dataset was generated from a suite of 33 bias-corrected GCM-RCM combinations for North America ran under full transient conditions with a historical period spanning 1950-2005, and with scenarios RCPs 4.5 and 8.5 for 2006-2100 at 0.22 and 0.44 degree resolution. The meteorological data from the climate models were bias-adjusted to match statistical characteristics of meteorological observations in the overlapping 1992-2022 period. The following meteorological variables are included: "sw" = Daily Mean Incoming shortwave at the surface (W m-2) "lw" = Daily Mean Incoming longwave at the surface (W m-2) "pr" = Daily Mean Total precipitation rate at the surface kg m-2 s-1) "qa" = Daily Mean Specific humidity at 2 m (kg kg-1) "wi" = Daily Mean Wind Speed at 6 m (ms-1) "ap" = Daily Mean Air Pressure at the surface (Pa) "tn" = Daily Minimum Air temperature at 2 m (°C) "tx" = Daily Maximum Air temperature at 2 m (°C) "ta" = Daily Mean Air temperature at 2 m (°C)
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| 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) | 0.012 | 0.008 |
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".