RENEWING MY MORTGAGE- How To Renew My Mortgage in 2023
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
RENEWING MY MORTGAGE- How To Renew My Mortgage in 2023 00:00 Intro 02:06 Changes to the Canadian Mortgage stress test rate for renewals 03:14 When should I start the mortgage renewal process 04:02 Should I stay with my bank or go with a mortgage broker 05:22 What is documents are required when I renew my mortgage 06:20 How can a mortgage broker help meIt has never been more important to get help with your mortgage renewal! Your existing lender might not be offering you your best renewal rate. Chatting to a mortgage broker can help you get the best rate at renewal time!If you have any questions in regards to this episode don't hesitate to email Ron ron@ronqmortgage.caTo connect with Ron and get started on a no-fee pre approval simply answer this simple questionnaire to get started! https://meetwithron.ca/ -Want to learn more about buying or investing in Saskatchewan Real Estate? Check out Ron Quaroni's new website for all the information you need! https://ronqmortgage.ca/ -To learn more about Saskatchewan Real Estate follow our social channels.Facebook https://www.facebook.com/RonQuaroni Instagram https://www.instagram.com/ronquaroni_... Linkedin https://www.linkedin.com/in/ronald-qu... Tik Tok https://www.tiktok.com/@thegoodbroker DisclaimerThe information in the video is for demonstrative purposes only. It does not take into account the specific objectives, circumstances and individual needs of the viewer. Its purpose is educational and should be relied upon in that regard. The information is believed to be reliable, but its accuracy, completeness and currency cannot be guaranteed. The authors and sources and any other party identified in the video do not assume any liability of any kind in connection with the information provided.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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