Crossing disciplinary boundaries in forest research: An international challenge
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
It is generally recognized that improving our understanding of forest-related research problems will involve amalgamating knowledge and methods from different disciplines. The presence of complex values within complex systems has persuaded many scientists engaged in forestry-related research to begin exploring cross-disciplinary paradigms in order to transcend the limitations of traditional disciplinary thinking. It has been suggested that authentic interdisciplinary programs in the sciences remain rare and that academic departments, academic supervisors and funding agencies present the main barriers to effective cross-disciplinary research among scientists. Despite these barriers, scientists around the world are increasingly approaching their research problems from a cross-disciplinary perspective to provide meaningful solutions to complex environmental problems. Key words: cross-disciplinary, interdisciplinary, forest research, complexity
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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