Leveraging system-integrator for better wood supply chain coordination through advanced planning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Natural and extensively managed forests supply raw materials to a diversified forest industry, requiring close coordination among mills when sharing the same procurement areas. One approach to enhance procurement planning process is by employing a system-integrator, a third-party organisation responsible for collaborative, fair, and neutral planning within the supply chain. Advanced planning and scheduling tools employing Operations Research methods can significantly improve wood procurement planning performance. This study aims to quantitatively and qualitatively evaluate the benefits of advanced tools on system-integrator’s decision-making. A Design Science Research approach was developed and tested with real data from a forest management company executing the annual procurement plan for 11 mills. Results indicate potential time reduction to harvest block selection and volume allocation, and transportation costs reduction by 15.44%, saving $2.16 per m³. Interviews with stakeholders confirmed that the proposed approach enhanced plan quality, planning process quality and system-integrator’s roles and characteristics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it