Changes in scale and bark stem surface injuries and mortality rates of a saguaro cacti (<i>Carnegiea gigantea</i>, Cactaceae) population in Tucson Mountain Park
Bibliographic record
Abstract
Rates that stem surfaces of saguaro cacti (Carnegiea gigantea (Engelm.) Britt & Rose) accumulate scale and bark injuries and the mortality rates of cacti were determined on a population of 1149 saguaro cacti in 50 field plots over the 9-year period of study (from 19931994 until 2002). Twenty-three percent of the saguaro population had few surface injuries throughout the 9-year period while 27% showed a marked increase in stem area with scale and bark injuries. Thirty percent of all cacti had more than 80% stem areas with combined scale and bark injuries on south-facing stem surfaces throughout the study period. Finally, 20.3% of the saguaro population died over the 9-year period, a rate of 2.3% per year. Thirty-three percent of all cacti that died by 2002 exhibited few surface injuries in 19931994 while 54% of the cacti that died over the period had more than 98% stem areas with combined scale and bark on south-facing stem surfaces in 19931994. In this manner, stem scale and bark injuries on south-facing surfaces were usually associated with the death of saguaros. The annual mortality rate of 2.3% appears high considering that this species may live for more than 200 years.Key words: saguaros, Carnegiea gigantea, Cactaceae, stem areas with scale and bark injuries, mortality rates.
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) | 0.001 | 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".