Measuring industrial lumber production using nighttime lights: A focus study on lumber mills in British Columbia, Canada
Bibliographic record
Abstract
Nighttime lights (NTL) are the procurement of remotely sensed artificial illumination from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite. NTL provides a unique perspective on anthropogenic activity by characterizing spatial and temporal patterns related to economic trends and human development. In this study, we assess the ability of NTL to characterize trends associated with industrial lumber production in British Columbia, Canada. We establish the presence of a logarithmic relationship between NTL and lumber mill production capacity (R2 = 0.69-0.82). The ability of NTL to temporally identify mill closures is then demonstrated by differentiating pairs of active and closed mills. We also identify Granger causality and co-integration between NTL and monthly lumber production, highlighting the predictive capability of NTL to forecast production. We then utilize this relationship to build linear regression models that utilize NTL data to estimate monthly (R2 = 0.33), quarterly (R2 = 0.58), and annual (R2 = 0.90) lumber production without reported data.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".