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
This paper presents an online educational game focusing on hierarchical procurement planning in a simulated forest supply chain with multiple companies. The purpose is to provide an understanding of the importance of individual decisions and their medium- to long-term impacts on the entire supply chain. The transportation game comprises three phases, each simulating hierarchical decision making when three competing companies (i.e., the game players) are making simultaneous decisions on the available resources. Each game phase also requires concurrent collaboration and competition. The phases represent different planning levels from long-term to short-term planning, considering the collaboration concept within the supply chain. The simulated supply chain objective is to minimize resource purchasing and transportation costs. The purchasing cost will be fixed after the first phase. The chance of decreasing transportation costs, however, is available until the end of the game. We develop three optimization models for each game phase. Once the game is finished, it compares the players’ results with optimal solutions prepared upfront. Finally, we present some comments about the game experience in various classrooms.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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