Shape outline extraction software (DiaOutline) for elliptic Fourier analysis application in morphometric studies
Bibliographic record
Abstract
PREMISE OF THE STUDY: Studies of plant cell and organ outline using shape analysis for taxonomic and morphological research have increased in the past decade. However, there are a limited number of available modern, intuitive, and easy software tools to conduct this work. METHODS: We developed a tool for shape outline extraction using MATLAB accompanied with R scripts to perform elliptic Fourier analysis. To demonstrate the shape tool, we applied the software and scripts for genera and species shape determinations of diatom (single cell) species with x-, y-, and x- + y-shape symmetries. RESULTS: Using the shape analysis tool, we were able to identify and distinguish different diatom taxa based on forms representing size diminutions associated with population changes. DISCUSSION: Independent of symmetry, species were successfully distinguished using supervised and unsupervised analyses. We hope that these shape analysis tools will be used to add another metric to plant science studies.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.016 |
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".