Bibliographic record
Abstract
Chickpea (Cicer arietinum L.) is an annual grain legume or 'pulse' crop used extensively for human consumption. Dried chickpea seed is commonly used in soup in India, while in the Middle East and elsewhere it is more frequently cooked and blended with rice dishes. The primary use in Syria is to prepare the homus bet-hina dish or falafel. Major chickpea producing countries include India, Pakistan, Mexico, Turkey, Canada, Syria, and Australia. Chickpea accounts for over 20% of world pulse production, and is the most important pulse crop after dry bean and pea. Chickpea provides important economic advantages to smallholder farm households: it is a source of protein (an alternative to meat) and a source of cash income, and improves soil quality when grown as a break crop in cereal-dominated farming systems. Despite the importance of chickpea, yields in Syria – and many other developing countries – have remained very low. The major constraints to productivity are the low yield potential of landraces, their susceptibility to biotic and abiotic stresses, and poor cultural practices. In Syria, chickpea is traditionally sown during spring on conserved soil moisture, if winter rainfall has been sufficient. Productivity is limited mainly by terminal drought and vascular wilt. With increasing pressure on land in Syria, profitability of spring chickpea is declining relative to other crops. This is a major reason for fluctuating or declining area and production.
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 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 | 0.001 | 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 | 0.001 | 0.001 |
| 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 teacher head, 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".