How Can We Improve <scp>M</scp>editerranean Cropping Systems?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In the M editerranean region, crop productivity and food security are closely linked to the adaptation of cropping systems to multiple abiotic stresses. Limited and unpredictable rainfall and low soil fertility have reduced agricultural productivity and environmental sustainability. For this reason, crop management technologies have been developed, with a special focus on the M editerranean region, to enhance crop production by increasing land productivity and sustaining soil fertility under influence of climate changes and population increases. The main objective of this study was to analyse dryland M editerranean cropping systems, and to discuss and recommend sustainable cropping technologies that could be used at the small‐scale farm level. Four crop management practices were evaluated: crop rotations, reduced tillage, use of organic manure, and supplemental and deficit irrigation. Among the tested interventions, incorporation of crop residues coupled with supplementary irrigation showed a significantly positive effect on crop productivity, yield stability and environmental sustainability.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 it