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
MEDICINE AN D THE COMMU NITYliving in “abject poverty and [were] forced to rely on minimal handouts from agencies and charities”.7 A quarter stated that they had been refused medical treatment owing to “their lack of status, funds or eligibility for medical assistance”. In response to the lack of equitable access demics. It consisted of two sections: (1) demographic characteristics and immigra-tion history; and (2) health issues recorded during the consultation (reasons for the encounter, tests, treatments, and referrals). Up to five reasons per consultation were recorded on the forms (if there were more had surgery that revealed that his cancer was inoperable. He is now having palliative chemotherapy through the same hospital and has been given a poor prognosis. His lack of access to health care delayed his diagnosis, worsened his outcome and increased the eventual cost of the care he needed. ◆ing the health and welfare needs of asylum seekers in Australia9,10 have been com-pounded by the lack of reliable data on the number of them who have no work rights and no Medicare access, mostly owing to the reluctance of the federal government to pro-vide these figures.11 In an audit of 102
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) | 0.002 | 0.001 |
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