Measurement of growth in the lichen<i>Rhizocarpon geographicum</i>using a new photographic technique
Bibliographic record
Abstract
Abstract Adobe® Photoshop® CS3 Extended software and a photographic time series were used to generate accurate and precise measures of change in the area, perimeter and diameter ofRhizocarponthalli at one, three and seven year intervals. Systematic measurements at a fixed grid of eight diameters per thallus showed a rapid and highly variable diametric growth phase in the smallest thalli (<5 mm2) and slower diametric growth (<0·01 mm2yr–1) in larger thalli (5–500 mm2). When standardized to an annual rate, the areal growth trend was similar, regardless of the number of years studied. This suggests that the areal and diametric growth of small and mid-sizedRhizocarponthalli may be insensitive to annual climatic variation and can be accurately characterized by repeat measurements taken over months rather than decades. Unlike diametric growth rate, change in thallus area and perimeter are statistically robust measures of growth inRhizocarponthalli. Our mean measurement accuracy was 99%. Measurement precision (reproducibility) was >95% (P>0·05) for thallus area and >96% for thallus perimeter. Our technique is tedious, but on flat rocks it can resolve and accurately measure change in thallus morphology at the sub-millimeter scale, and it can be used with recent and/or historical images.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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 | 0.001 |
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".