Bibliographic record
Abstract
Structure is formed by components.Components are division units, connectors, joints and boundaries which are formed by transformators, around regulators and in adherence to principles.Such a structure has meaning.Meaning is a subjective which is perceived by the reader through a word, sentence, paragraph or text.The meaning structure is a network of semantic units which are formed by transformators, around regulators and in adherence to principles.Likewise, the physique structure of city is a total, consisting of Physique which are formed by transformators, around regulators, and in adherence to the principles.In this study, Yazd i historical context is the case study.The physique structure of Yazd historical context has been designed in compliance with rich patterns.This study is about to answer the question: What are the patterns of components of the corresponded structure of physique-Meaning in Yazd historical context?And how these patterns can be identified?The study of this context has been done through the samples in three levels.In this study, after describing the characters of the structure components and calculating the correlation between them, similarities and differences of the characters are categorized based on one or some characteristics and one specification and represented as patterns.This study has been performed by survey, descriptive and correlative methods.The conclusion of studies categorized the meaningful patterns which are formed in the physique structure of the context in accordance with behaviors, value criteria, and society and in general based on facilities, needs and demands of people.These patterns could be used in redesigning of the context.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.962 | 0.977 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".