Real Estate Tips & Advice for October 1st, 2020
Bibliographic record
Abstract
???? ?????????????????????????? ???????? ???????????? ???????? ?? Real estate markets in the U.S. are quite hot right now. Buyer demand far exceeding inventory. Low interest rates and seller reluctance to sell are the key reasons given.???? ???????????????? ???????? ???????????? ???????? ?? Moody's Analytics expects Canada's real estate value to take a downturn next year, especially in Calgary & Edmonton (10%), Toronto (9%) and Vancouver (7%). Smaller markets are expected to fare better, due to increased demand for larger homes and more space at affordable prices. (Winnipeg)??️ ???????????????? ???????? ???????????? ???????? ?? Winnipeg remains a hot sellers market, especially for houses under 400K. High buyer demand and 45% fewer listings than last year same time. Pandemic stage orange has been instituted and masks are mandatory in public places. Still going to Open Houses? Be careful out there.☎️ ?????????? ???????? ???????? ???????????????? ???????? ?? Mike Schroeder of Mortgage Architects tell us about alternatives to CMHC, which include Canada Guarantee and Genworth. Both of these allow buyers to buy 'more house' than CMHC. Mortgage Brokers offer access to all three insurers, which can help buyers, especially ones with bruised credit or new to Canada. ?? ???????? ???????? ???? ?????? ???????? ?? New post titled \\"8 things you can do to protect your plants this winter\\". Winter is coming, and protecting your plants will help them thrive in the spring. ?? ?????????????????? ???? ?????????? ???????????????? ?? It's time to check your furnaces. By signed up to Aire-Serv Heating and A/C Maintenance Plan, you get a furnace check and clean now, plus an A/C check in the springtime. Also included is a 10-15% discount on any needed repair parts and labour. All for $190 plus taxes. Go to Aire-Serv Heating and A/C ?? ?? ?????????? ???????????????? ?????? ?????????? ?? Next week we'll have another call with Mortgage Mike, more news and updates, as well as answering a listeners question: \\"How to upgrade my 1980's house\\".For more real estate info, check my blog at https://blog.winnipeghomefinder.comNever miss an episode. Install our FREE Podcast App available on iOS and Android.For your Apple Devices, click here to install our iOS App.For your Android Devices, click here to install our Android App.Check my videos on Youtube
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.264 | 0.011 |
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".