The influence of jack pine tree and tissue age on the establishment of infection by the jack pine dwarf mistletoe, <i>Arceuthobium americanum</i>
Bibliographic record
Abstract
The purpose of this study was to test the hypothesis that infection of jack pine (Pinus banksiana Lamb.) by jack pine dwarf mistletoe (Arceuthobium americanum Nutt. ex Engelm.) increases with increasing tree age and decreases with increasing tissue age. One-, 2-, and 3-year-old tissues of 3-, 5-, and 7- year-old jack pines and 1-, 4- and 8-year-old tissues of 12-, 17-, and 22-year-old jack pines in Belair Provincial Forest were inoculated with seed of A. americanum in September of 1992 (year 1) and 1993 (year 2). Overwinter and postwinter seed removal, fungal and insect damage, and infection success were monitored from the time of inoculation to harvesting of inoculated branches. In years 1 and 2, overwinter seed displacement was 12.2 and 30.6%, while postwinter loss was 28.8 and 22.2%, respectively. Seed germination ranged from 14.3 to 38.1% and from 3.1 to 17.5%, respectively, in years 1 and 2. Infection success varied from 2.0 to 35.0% (year 1) and from 0.0 to 13.0% (year 2). Lower mean daily temperatures in January and February (p < 0.001) were hypothesized to have killed more seeds and thereby reduced infection success in year 2. Infection success did not increase with increasing tree age (year 1: p = 0.188; year 2: p = 0.807) in either year of the study. Infection success increased with increasing tissue age in year 1 (p < 0.001) but not in year 2 (p = 0.358). We rejected the hypotheses that susceptibility to infection by A. americanum increases with increasing tree age or decreases with increasing tissue age of jack pine. Infection success appears to be primarily dependent upon seed displacement caused by wind, snow, or rain.Key words: jack pine, dwarf mistletoe, infectivity, juvenile resistance, seed displacement.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".