Additional file 1 of Design and fabrication of an improved dynamic flow cuvette for 13CO2 labeling in Arabidopsis plants
Bibliographic record
Abstract
Additional file 1: Fig. S1. Spectral output of light emitting diodes (LEDs) used in growth chamber and labeling experiments. The measured light spectrum of natural sunlight is provided for comparison. All spectra were measured with a Licor LI-180 radio spectrometer. PPFD, photosynthetically active photon flux density (μEinsteins m-2 s-1). Fig. S2. Schematic of cuvette design created in Fusion360 (Autodesk). All dimensions are shown in mm. Fig. S3. Relative distribution of 13C labeled isotopologs of the central metabolic intermediates described in Figure 5 during a whole plant time-course labeling series. A, Relative isotopolog abundance of triose phosphate. B, Relative isotopolog abundance of MEcDP. C, Relative isotopolog abundance IDP & DMADP. See “Methods and materials” for additional details on the acquisition of metabolite labeling data. Fig. S4. Representative LCMS/MS and GCMS chromatograms of 13C labeled plant metabolites analyzed in this study. A-D were acquired by LCMS/MS in multiple reaction monitoring mode and E by GCMS. A, Separation of triose-phosphate and glycerol 3-phosphate standards (black line = m/z 169 → 79; orange line = m/z 171 → 79). B, Triose-phosphate in labeled Arabidopsis extracts showing individual isotopologs (m/z 169 – 172 → 79) after 30 min labeling and their separation from glycerol-3-phosphate (m/z 171 → 79). A and B were resolved on a Luna C-18(2) column (100 mm × 2.0 mm, 2.5 mm particle size; Phenomenex) (see “Methods and materials”). C, Analysis of 2C-methyl-D-erythritol-2,4-cyclodiposphate (MEcDP, m/z 277 → 79). D, Isopentenyl and dimethylallyl diphosphate (IDP+DMADP, m/z 245 → 79). C and D were separated on a HILIC column. E, GCMS analysis of (-)-isomenthone in a Pelargonium graveolens leaf surface extract.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.831 | 0.205 |
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".