Design and implementation of a cuvette system for light analysis of photosynthetic pigments
Bibliographic record
Abstract
Studying photosynthetic pigments is essential in understanding the mechanisms of photosynthesis; an important aspect of this is the examination of the absorption characteristics of these pigments, and the nature of their interaction with light. The need and requirements of a modular, flexible cuvette system were investigated by performing light absorption tests with photosynthetic pigments. A proposed in-house design was conceived and implemented after determining the appropriate requirements and dimensions of the system by running tests with a commercial spectrometer and with the LED light sources and spectroradiometer readily available at McGill University to maximize compatibility and reduce the cost of the new system. A series of tests were performed using blank mineral oil and water samples, and two types of glass cuvettes with the new system. The angles of light incidence were varied, with each combination of solvent and cuvette undergoing testing at vertical and horizontal angles, in addition to four other angles. The obtained results show the occurrence of a lensing effect; this effect amplifies light intensity, and is influenced by the shape and material of the cuvette container, the type of solvent used, and the tested angle of incidence. The cylindrical shape of the cuvette combined with a mineral oil sample results in a high and significant increase lensing, while the rectangular cuvette shows some amplification when using water based sample. The building procedure and results of the new system, as well as the recommendation for future improvements are detailed in this thesis
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".