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Record W2900057823 · doi:10.3390/f9110693

The 2018 Woody Crops International Conference, Rhinelander, Wisconsin, USA, 22–27 July 2018

2018· article· en· W2900057823 on OpenAlexaff
Emile S. Gardiner, Solomon B. Ghezehei, William L. Headlee, Jim Richardson, Raju Soolanayakanahally, Brian J. Stanton, Ronald S. Zalesny

Bibliographic record

VenueForests · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsAgriculture and Agri-Food Canada
FundersNational Council for Air and Stream Improvement
KeywordsBioproductsBiomass (ecology)Library scienceEngineeringBiofuelEcologyBiologyComputer scienceWaste management

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.033
GPT teacher head0.252
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2018
Admission routes1
Has abstractyes

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