Exposing the Origins of Irreproducibility in Fluorine NMR Spectroscopy
Bibliographic record
Abstract
Abstract Fluorine chemistry has taken a pivotal role in chemical reaction discovery, drug development, and chemical biology. NMR spectroscopy, arguably the most important technique for the characterization of fluorinated compounds, is rife with highly inconsistent referencing of fluorine NMR chemical shifts, producing deviations larger than 1 ppm. Herein, we provide unprecedented evidence that both spectrometer design and the current unified scale system underpinning the calibration of heteronuclear NMR spectra have unintentionally led to widespread variation in the standardization of 19 F NMR spectral data. We demonstrate that internal referencing provides the most robust, practical, and reproducible method whereby chemical shifts can be consistently measured and confirmed between institutions to less than 30 ppb deviation. Finally, we provide a comprehensive table of appropriately calibrated chemical shifts of reference compounds that will serve to calibrate 19 F spectra correctly.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".