The Priorities of Landscape Architectural Elements and the Decision to Use City Park Spaces (Case Study: Somdej Phra Sri Nagarindra 84 Parks, Thailand)
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
This article aims to prioritize and assess each architecture element to ensure its compliance with the users’ needs, leading to interaction, and holistic interrelation as well as systematic solutions. As a result, fundamental data, and needs for the landscape architecture elements, were collected using a structured questionnaire with residents living in Muang District, the main service district. A structured interview was conducted with current visitors to the park and collected data concerning physical components for collaborative analysis. Article findings suggested that the elements are ranked and put into three groups: Group 1, the element of providing access, Group 2, the element of leading to activities, and Group 3, the element of creating a good environment. Consistent and more frequent visits represent the success of a designer. The designer could prioritize and assess each component to ensure compliance with the users’ needs, leading to interaction, holistic interrelation, and systematic solutions.
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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it