Rentez: A Simplified Rental App Experience Designed to Promote Transparency and Verification
Bibliographic record
Abstract
Each year many international students arrive in Canada with dreams of outstanding academic and professional careers but are met with a sad reality: the time-consuming and inconvenient process of finding suitable accommodation. There are currently a large number of unverified rental posts on platforms such as Facebook Marketplace and Kijiji, where renters are frequently confused by listings that lack adequate information/details or are outright fraudulent. This project aims to design an optimized rental app that will allow renters to find legitimate sources of rental properties. Most importantly, it will ensure communication between the renter and the listing/ad owner. This Major Research Project will investigate the ways in which user experience design might be utilized to address the issues that users face in the real world. This incorporates both research and analytical work. Additionally, wireframing and prototyping, as well as other types of design thinking, were investigated throughout the course of this paper. Methods pertaining to the user experience and the user interface were implemented in this project to create an interactive and seamless experience.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".