Bibliographic record
Abstract
Metal acetylacetonates are coordination complexes of metal ions and the acetylacetonate anion with diverse uses including catalysts, cross-linking agents and adhesion promotors. Some metal acetylacetonates can photostabilize polymers whereas others are photocatalysts. We hypothesize that the ability of metal acetylacetonates to photostabilize wood will vary depending on the metal in the coordination complex. We test this hypothesis by treating yellow cedar veneers with different acetylacetonates (Co, Cr, Fe, Mn, Ni, and Ti), exposing veneers to natural weathering in Australia, and measuring changes in properties of treated veneers. The most effective treatments were also tested on yellow cedar panels exposed to the weather in Vancouver, Canada. Nickel, manganese, and titanium acetylacetonates were able to restrict weight and tensile strength losses and delignification of wood veneers during natural weathering. Titanium acetylacetonate was as effective as a reactive UV absorber at reducing the greying of panels exposed to 6 months of natural weathering, and both titanium and manganese acetylacetonates reduced the photo-discoloration of panels finished with a polyurethane coating. We conclude that the effectiveness of metal acetylacetonates at photostabilizing wood varies depending on the metal in the coordination complex, and titanium and manganese acetylacetonate show promise as photoprotective primers for wood.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".