DISTINGUISHING NATIVE AND PLANTATION-GROWN MAHOGANY (SWIETENIA MACROPHYLLA) TIMBER USING CHROMATOGRAPHY AND HIGH-RESOLUTION QUADRUPOLE TIME-OF-FLIGHT MASS SPECTROMETRY
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
Plantation-grown mahogany (Swietenia macrophylla) from Fiji has been preferred as a sus- tainable wood source for the craftingof electric guitars because its trade is not restricted by Convention on International Trade in Endangered Species of Wild Fauna andFlora (CITES), unlike S. macrophylla sourced from native forests. Ability to differentiate between the two wood types would deter sale of illegally harvested native-grown S. macrophylla to luthiers and other artisans. The chemical composition of wood is influenced bycambial age and geographical factors, and there are chemical differences between S. macrophylla grown in different regions. Thisstudy tested the ability of high-resolution mass spectrometry to chemotypically dif- ferentiate plantation-grown Fijian S. macrophylla from the same wood species obtained from native forests. Multiple heartwood specimens of both wood types were extracted and chromatographically profiled using gas and liquid chromatography tandem high-resolution quadrupole time-of-flight massspectrometry (GC/QToF, LC/QToF). Visual comparison of mass spectral ions, together with modern analytical data-mining techniques,were employed to screen the results. Principal component analysis scatter plots with 95% confidence ellipses showed unambiguousseparation of the two wood types by GC/LC/QToF. We conclude that screening of heartwood extractives using high-resolution massspectrometry offers an effective way of identifying and sepa- rating plantation-grown Fijian S. macrophylla from wood grown in native forests.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it