Deciphering the Structural Complexity of <i>Populus</i> Secondary Cell Walls: Implications for Biomass Conversion Efficiency
Bibliographic record
Abstract
The paper titled "Atomistic, macromolecular model of the Populus secondary cell wall informed by solid-state NMR" was published on January 3, 2024, in the open-access journal Science Advances, under the Science Publishing Group. The authors, Bennett Addison, Lintao Bu, Vivek Bharadwaj, Meagan F. Crowley, Anne E. Harman-Ware, Michael F. Crowley, Yannick J. Bomble, and Peter N. Ciesielski are from National Renewable Energy Laboratory and the Colorado School of Mines in Golden, CO, USA. The study presents an atomistic macromolecular model of the secondary cell wall (SCW) in Populus wood, focusing on the interactions and configurations of cellulose, hemicelluloses, and lignin. Utilizing solid-state nuclear magnetic resonance (ssNMR) measurements, the research investigates the structural configurations and intermolecular interactions within the SCW. This information is used to develop and refine molecular models through molecular dynamics (MD) simulations, enhancing the understanding of the SCW's architecture and informing biomass deconstruction strategies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".