Plant blindness profile of high school students in Hulu Gurung sub-district, Kapuas Hulu district
Bibliographic record
Abstract
People often forget about plants as living organisms that are essential for life which characterizes plant blindness. Plant blindness can occur in students. The objectives of this study are identifying plant blindness in high school student in Hulu Gurung. This research was conducted in January 2023 in the even semester of 2022/2023. The population in this study were all students of SMPN 1 Hulu Gurung (Junior High School) and SMAN 1 Hulu Gurung (Senior High School). Sample selection using Simple Random Sampling technique. The instruments used were questionnaires and direct interviews. Methods for data analysis using qualitative descriptive methods. The results showed that students still lack knowledge about local vegetables. The percentage of students recognizing vegetables was 15% in senior high school students and 4% in junior high school students. There were 6 vegetable species that were not recognized at all, namely Solanum lasiocarpum, Ficus sp., Mangifera pajang, Polypodium sp., Ficus sp., and Smilax leucophylla. In the future local vegetables can be better recognized amidst the presence of imported vegetables. The diversity of local vegetable crops must be maintained through conservation strategies, one of which is to avoid plant blindness as early as possible.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".