Quantification of additive response and stationarity of frost hardiness by photoperiod and temperature in Scots pine
Bibliographic record
Abstract
To present quantitative knowledge of photoperiod and temperature on frost hardiness for mathematical modelling, we carried out a growth chamber experiment for second-year Scots pine (Pinus sylvestris L.) seedlings. There were three treatments involved in the trial: a short photoperiod (7 h light : 17 h dark cycle) with a high temperature (15 °C) (SDHT), a short photoperiod (7 h light : 17 h dark cycle) with a low temperature (2 °C), and a long photo period (16 h light : 8 h dark cycle) with a low temperature (2 °C). The following variables were measured: (i) the frost hardiness of stems, needles, buds, and roots by controlled freezing tests, (ii) the electrical impedance spectroscopy (EIS) parameters of the stems, (iii) the chlorophyll fluorescence (Fv/Fm) of the needles, (iv) the dry mass/fresh mass ratio, and (v) the total soluble sugar and starch concentration of the stems, needles, and roots in the non-frost-exposed organs. There was a clear difference in hardiness among the organs by the end of the experiment. Stems by some EIS parameters, needles by Fv/Fm, and stems, needles, and roots by sugar concentration differed among treatments. A stationary level of frost hardiness was reached or asymptotically approached in all organs and treatments except in the SDHT treatment of buds. Very little support was found for the concept of additive effects by photoperiod and temperature. The results show that the additive model needs revision, since the hardening response is dependent on organ, and there is an interaction in the responses to photoperiod and temperature.
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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 | 0.001 |
| 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) | 0.000 | 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".