A simple mathematical model to aid quantification of electrophoresis gels by image analysis
Bibliographic record
Abstract
In many scientific disciplines, measurements are taken from films that have been exposed to energetic sources. Examples include radiographs where the source is an X-ray tube, autoradiography where the source is a radioactive isotope and electrophoresis gels where the source is an enhanced chemiluminescence reaction. In these situations it is of interest to quantify the darkening of the film and compute the strength of the source which in the cases of autoradiography and electrophoresis can be used to compute unknown concentrations of biochemicals. We developed a simple mathematical model of the darkening of films in radiography, autoradiography and electrophoresis bands disclosed by enhanced chemiluminescence, and present formulae to calculate the strength of the source from measurement of film blackening by image analysis. A simple model is used in two examples to predict blackening of film exposed to electromagnetic radiation. This blackening is measured by image analysis. Results show reasonable agreement between predictions of the model and blackening of film for the examples chosen. This model is proposed as an aid to quantification of electrophoresis gels.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.002 | 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 teacher head, 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".