Bibliographic record
Abstract
This paper provides the tools for distinguishing levels of tolerance to root‐zone salinity in agricultural crops. Such distinction rests on the response of a crop's product yield following the declining, sigmoid‐shaped, modified compound‐discount function {Yr = 1/[1 + (C/C50)exp(sC50)]} for plants grown as crops exposed to increasing root‐zone salinity. This nonlinear function relates relative yield (Yr) to root‐zone salinity (C) measured in equivalent saturated soil‐paste extract electrical conductivity with two nonlinear parameters, the salinity level producing 50% of the nonsaline crop yield (C50) and a response curve steepness constant (s) equal to the absolute value of the mean dYr/dC from Yr = 0.3 to 0.7. These discount parameters suggest the existence of a single‐value salinity tolerance index (ST‐Index) equal to the 50% reduction in crop yield from that of the nonsaline yield plus a tendency to maintain some product yield as the crop is subjected to salinity levels approaching C50, i.e., ST‐Index = C50 + s(C50). The explicit purpose of this study is to determine if the discount function using biophysically relevant parameters can be applied to historical data sets. Approximations for C50 and s were identified in the threshold salinity (Ct) and declining slope (b) parameters of the well‐known threshold‐slope linear response function. Several procedures for converting Ct to C50 and b to s offer the linkage between these linear and nonlinear response functions. From these procedures, two regression equations, C50 = 0.988[(0.5/b) + Ct] − 0.252 and s = 1.52b, proved the most appropriate for the eight representative field, forage, and vegetable crops tested. The selected conversion procedures were applied to previously published Ct and b values to obtain a list of the relative root‐zone salinity tolerance in agricultural crops. In addition to C50 and s, values for exp(sC50) and the ST‐Index were computed for each crop. The revised list provides extension personnel and plant growth modelers the parameter values from a nonlinear analog of crop yield response to root‐zone salinity.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".