INTEGRASI STRUKTUR DAN FUNGSI BAGIAN TUMBUHAN DENGAN BAYANI, BURHANI, ‘IRFANI DI SDIT BUNAYYA
Bibliographic record
Abstract
AbstractPlants are living things that do not experience the activity of moving like humans and animals, but they can reproduce in their own way. The parts that are in plants are always different from one another, this is influenced by climatic factors and geographic areas. Areas that have lots of sunlight will be different from plants that live in areas with cool weather or below 20 degrees Celsius. Based on the issues that have developed in education during this decade, this paper will try to develop science material on "Structure and Function of Plant Parts" in SDIT Bunayya students. If the main source (origin) of science in the Bayani approach is text (revelation), then in the 'irfani approach the main source is experience (experience), which is an authentic life experience, and is actually an invaluable lesson. Inner experiences that are very deep, authentic, innate, and almost unspeakable by logic and cannot be expressed by language. This is what is called direct experience, and is called hudhri science in the isyraqiyyah tradition. All these authentic experiences can be felt directly without having to say it first through the expression of "language" or "logic". Keywords: integration; plants; bayani; burhani; and 'irfani.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".