Detect Structure Features of Asymmetric and Symmetric CH2 and CH3 Functional Groups and Their Ratio of Biopolymers within Intact Tissue in Complex Plant System Using Synchrotron FTIRM and DRIFT Molecular Spectroscopy
Bibliographic record
Abstract
Synchrotron light is photon beam, which is million times brighter than sunlight. A synchrotron facility is a giant particle accelerator that turns electrons into light (Wikipedia, 2010). How a Synchrotron Works? Electric Gun (EG: Synchrotron Component 1) in a synchrotron blasts out electrons. The electrons are accelerated to nearly speed of light by Linear Accelerator (LA: Synchrotron Component 2). A small synchrotron orbiting Booster Ring (BR: Synchrotron Component 3) increase their energy. Finally electron bunches enter Storage Ring (SR: Synchrotron Component 4). The bunches orbit ring controlled by serial magnets. Special magnet called "Undulator" causes electrons to rapidly change course and vast emitting energy in form of photons. Then photons enter Beamline (BL: Synchrotron Component 5) and directed to device called "monochromator" which selects specific wavelength required for each experiment. Finally, light focus onto sample at Experimental End Station (ES: Synchrotron Component 6), where scientists collect data to determine molecular structure The extremely bright synchrotron light makes it possible to detect biomaterial structure (make-up or conformation) at both molecular and cellular levels (Marinkovic & Chance, 2006;
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".