Soil Quality Evaluation of Inceptisol Based on the Alberta Card (Case Study of Horticultural Land in Titi Papan, Medan Deli District)
Bibliographic record
Abstract
Soil quality describes the suitability of the physical, chemical, and biological properties of soil that together function as a medium for plant growth. The Alberta Soil Quality Card is one method for evaluating soil quality through soil quality indicators, such as organic matter content, drainage, water-holding capacity, soil microorganisms, and erosion. This research was conducted to evaluate the Inceptisols soil quality of horticulture land in Titi Papan, Medan Deli District, based on the indicators listed in the Alberta Soil Quality Card to obtain appropriate soil management recommendations based on the evaluation results. The results of soil quality observation in the horticultural land of Titi Papan, Medan Deli District, indicate that the preferred score (P) is found in the indicators of plant/weed strength, nurseries, soil fertility, and salinity. A medium score (M) is obtained in the indicators of residue cover, organic material color, drainage/infiltration, aggregation, and soil life, including the presence of worms, compaction/rooting, and water erosion. The limiting factor with a low score (L) is obtained in the indicator of water holding capacity.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".