Časoprostorová analýza dat z prodeje obytných nemovitostí s využitím časoprostorové kostky v ArcGIS
Bibliographic record
Abstract
This bachelor thesis deals with the spatio-temporal analysis of data related to residential property sales in the province of British Columbia, Canada.The thesis is particularly focused on data visualizations using a tool called a space-time cube, which is implemented into ArcGIS Pro software.The analysis is being performed for the assessment purposes of Landcor Data Corporation, which has provided us with the data.The theoretical section introduces methods of spatio-temporal analyses and analyses focused on the sale of residential properties.In the practical section, the space-time cube tool is applied to the available data.The results of this thesis are static maps, charts and 3D visualizations, as well as a map project in .ppkxformat that enables interactive data analysis.
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 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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.015 | 0.016 |
| Meta-epidemiology (broad) | 0.013 | 0.005 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.013 | 0.008 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.046 | 0.208 |
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; both teacher heads 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".