Resveratrol Photoisomerization: An Integrative Guided-Inquiry Experiment
Bibliographic record
Abstract
A kinetic study of trans–cis resveratrol photoisomerization was developed as a model guided-inquiry experiment for third-year undergraduate students to bridge the gap between explicitly prescribed laboratories and independent fourth-year research projects. Resveratrol photoisomerization was performed directly in a NMR tube within a UV photochemical reactor during which aliquots of sample were removed and diluted at specific time intervals for UV absorbance and HPLC measurements, whereas NMR spectra were performed directly in the original sample. Students in small groups are directly involved in the planning and organization of the experiment along with subsequent data analysis to statistically compare the apparent rate constant and half-life. Students appreciate the advantages and limitations of each technique with respect to quantitative and qualitative analyses, as well as understanding the photochemical properties of a recently discovered natural phytochemical with important biological properties relevant to human health. Students are also provided the opportunity to repeat the experiment to improve their technique and assess the reliability of their results. Our main objective was to promote inquiry-based learning in students within a defined experimental setting that integrates several fundamental concepts and instrumental techniques as a way to better prepare students for independent research in chemical biology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".