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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.239 | 0.060 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".