Characterization of humic substances by matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry
Bibliographic record
Abstract
Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) and laser desorption/ionization (LDI-)TOFMS have been used to characterize Suwannee River humic substances, obtained from the International Humic Substances Society (IHSS), and Armadale soil fulvic acid (ASFA). An array of MALDI matrices were tested for use with humic substances, including alpha-cyano-4-hydroxycinammic acid (CHCA), 2-(4-hydroxyphenylazo)benzoic acid (HABA), 2,5-dihydroxybenzoic acid (DHBA), sinapinic acid, dithranol and norharmane. DHBA yielded the best results, exhibiting superior ionization efficiency, low noise, broad applicability to the analytes of interest, and most importantly producing an abundance of high mass ions, the highest observed being m/z 1848. A number of sample preparation modes were investigated; the overlayer method improved sample/matrix homogeneity and hence shot-to-shot reproducibility. The choice of the matrix, mass ratio of analyte to matrix, and the sample preparation protocol, were found to be the most critical factors governing the quality of the mass spectra. Matrix suppression was greatly enhanced by ensuring good mixing of matrix and analyte in the solid phase, proper optimization of the matrix/analyte ratio, and optimizing delayed extraction to ensure complete matrix-analyte reaction in the plume before ions are moved to the flight tube. A number of common features, in particular specific ions which could not be attributed to the matrices or to contaminants, were present in the spectra of all the humic substances, regardless of origin or operational definition. Additionally, a prominent repeating pattern of peaks separated by 55, 114 and 169 Da was clearly observed in both LDI and MALDI, suggesting that the humic compounds studied here may have quasi-polymeric or oligomeric features.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".