X‐ray photoelectron and carbon Kα emission measurements and calculations of O‐, CO‐, N‐, and S‐containing substances
Bibliographic record
Abstract
Abstract X‐ray fluorescence measurements for O‐containing [polyethylene oxide, polyvinyl alcohol, polyvinyl methyl ether], CO‐containing [polyvinyl methyl ketone, polyethylene terephthalate], N‐containing [poly‐4‐vinylpyridine (P4VP), polyaniline oligomer (PAO)], and S‐containing [polyphenylene sulfide] substances are presented. Carbon Kα X‐ray emission spectra (XES) and X‐ray photoelectron spectra (XPS) are compared with our DFT calculations performed with the Amsterdam density functional (ADF) program. The combined analysis of valence XPS and carbon Kα XES allows us to determine the individual contributions from pσ‐ and pπ‐bonding molecular orbitals of the polymers. The ΔSCF calculations yield the accurate C1s core‐electron binding energies (CEBEs) for all carbon sites of the organic compound. We calculate all CEBEs of the model molecules using the ΔEKS approach. Our simulated C1s photoelectron and C Kα emission spectra are in good agreement with our measurements. We also obtain WD (work function and the other energies) values for the polymers and PAO from the difference between calculated (gas‐phase) and measured (solid) CEBE values. © 2006 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 45: 162–172, 2007
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".