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
In July 2016, a Calgary mother, Sara Baillie, was found dead in her home, and her five-year-old daughter, Taliyah Marsman, was missing.Three days later, an Amber Alert came to a heartbreaking end when the little girl was found dead.On this episode of Global News podcast Crime Beat, crime reporter Nancy Hixt takes a look at who killed Sara and Taliyah.Hours after Taliyah's body was recovered, police announced a man was charged in the case.Edward Downey was accused of two counts of first-degree murder.Sara and Taliyah's family was left with so many questions.The man accused of this incomprehensible crime wasn't even on the family's radar.Why would Downey kill Sara, let alone her child?For more details on the case check this out https://wp.me/p2Y4rw-nJ4MIf you enjoy Crime Beat, please take a minute to rate it on Apple Podcasts or Google Podcasts, tell us what you think and share the show with your friends.Contact:Twitter: @nancyhixtFacebook: https://www.facebook.com/NancyHixtCrimeBeat/Email: nancy.hixt@globalnews.caLearn more about your ad choices. Visit megaphone.fm/adchoices
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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.541 | 0.059 |
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