Top-Down Lipidomic Screens by Multivariate Analysis of High-Resolution Survey Mass Spectra
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
Direct profiling of total lipid extracts on a hybrid LTQ Orbitrap mass spectrometer by high-resolution survey spectra clusters species of 11 major lipid classes into 7 groups, which are distinguished by their sum compositions and could be identified by accurately determined masses. Rapid acquisition of survey spectra was employed as a "top-down" screening tool that, together with the computational method of principal component analysis, revealed pronounced perturbations in the abundance of lipid precursors within the entire series of experiments. Altered lipid precursors were subsequently identified either by accurately determined masses or by in-depth MS/MS characterization that was performed on the same instrument. Hence, the sensitivity, throughput and robustness of lipidomics screens were improved without compromising the accuracy and specificity of molecular species identification. The top-down lipidomics strategy lends itself for high-throughput screens complementing ongoing functional genomics efforts.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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