Inovasi dalam Teknik Irigasi dan Dampaknya terhadap Hasil Pertanian: Kajian Bibliometrik
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
Penelitian ini menunjukkan bahwa inovasi dalam teknik irigasi secara signifikan mempengaruhi hasil pertanian dan efisiensi penggunaan sumber daya. Dengan fokus pada teknologi terkini seperti irigasi defisit, irigasi tetes, dan otomatisasi berbasis IoT, riset ini mengungkap bagaimana teknik-teknik ini dapat meningkatkan produktivitas pertanian sambil mengurangi konsumsi air. Temuan ini menegaskan pentingnya integrasi teknologi canggih dalam praktik irigasi untuk menghadapi tantangan global seperti keamanan pangan dan perubahan iklim. Melalui analisis bibliometrik, penelitian ini juga menyoroti kebutuhan akan pendekatan multidisiplin dan kolaborasi lintas sektor dalam mengembangkan solusi berkelanjutan untuk pengelolaan sumber daya air di pertanian.
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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.048 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.009 |
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