Direct Infusion Mass Spectrometric Analysis of Bio-oil Using ESI-Ion-Trap MS
Bibliographic record
Abstract
Direct infusion-electrospray ionization (ESI)-Ion-Trap MS and ESI-Ion-Trap MS 2 were used for direct analysis of bio-oil from forest residue and reference bio-oils from cellulose and hardwood lignin. It was found that the bio-oil concentration and mode of MS analysis are important parameters in obtaining reproducible and structurally informative data. In order to study sensitivity and selectivity with ESI-Ion-Trap MS, a selection of model compounds were studied with and without dopants. Dopants included NaCl, formic acid and NH 4 Cl in positive ion mode and NaOH and NH 4 Cl in negative ion mode. NH 4 Cl addition can be used to distinguish carbohydrate-derived products from other bio-oil components. NaOH and NaCl additives produced the highest peak intensities in negative ion mode as deprotonated adducts and in positive mode as sodiated adducts, respectively. ESI-MS 2 was used successfully for confirmation of individual target ions such as levoglucosan and cellobiosan, as well for some structural products of lignin. Simple bio-oil fractionation into hydrophilic and hydrophobic components provided less complex and more interpretive ion spectra.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".