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
Why is now the start of the spring market in Winnipeg? Hear of the two most recent sales, and the stats that tell the story.For more real estate info, check my blog at https://blog.winnipeghomefinder.com Never 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 YoutubeLooking after and reporting on historic stats is easy..... extrapolating information from those stats, and predicting the future is harder. UnlessA few very loud and obvious facts jump out, making it easier to interpret. For example:2 weeks ago I listed a bungaow in the west st james area for $250,000.It ended up with 45 showings and 15 offers, and sold for $30grand over asking.But one example does not make a trendSo this past week, I listed another bungalow, this one in north kildonan, for $260K.46 showings, 10 offers and sold for 23K above asking.So 91 showings, and 25 offers on these two listings. Seeing a trend? Two different parts of the city, but both homes are smack in the middle of Winnipeg's most popular price range category....Why is this happening?Well, let's look at available listings.Last year, this time, we had 1635 homes for sale in Winnipeg.Today, that number is 1273. That is 22% fewer listings than the same time last year.So if you're thinking of selling your Winnipeg home, NOW is the perfect time. Listings are down, but buyer activity (91 showings, 25 offers on two homes) is up.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.447 | 0.005 |
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