The 2018 Woody Crops International Conference, Rhinelander, Wisconsin, USA, 22–27 July 2018
Bibliographic record
Abstract
The 2018 Woody Crops International Conference was held from 22 to 27 July 2018 throughout Minnesota and Wisconsin, USA to unite world-leading short rotation woody crop (SRWC) organizations at a forum designed to enhance information exchange while also building a platform for developing future collaboration around SRWC production systems. The meeting included pre-conference and post-conference tours in Minnesota and Wisconsin and technical sessions in Rhinelander, Wisconsin. Technical sessions were framed under the topics: Genetics and Physiology, Phytotechnologies, Stakeholders, Bioproducts, Harvesting and Logistics, Biomass Production, and Ecosystem Services. This Conference Report provides a compilation of abstracts from each of the 38 oral and poster presentations delivered during the technical program. It should serve to enhance future discussions among scientists, academicians, regulators, and the general public relative to sustainable application of SRWC technologies for a multitude of current objectives.
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.
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 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.118 | 0.029 |
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".