Bibliographic record
Abstract
It was in 1996. The manuscript for the first edition of this Training Manual, produced under the auspices of Health Canada and the Canadian Psychiatric Association, was being completed. Many clinicians caring for HIV-infected individuals were becoming demoralized. The nucleoside reverse transcriptase inhibitors (NRTIs), the only class of antiretrovirals available at the time, were failing to make a significant impact on mortality. The full implication of the development of resistance to these medications was being felt. Then, a second class of antiretroviral agents, the protease inhibitors (PIs) became available. Clinical trials were initiated and, at the International AIDS Conference held in Vancouver (Canada) in 1997, it became clear that a turning point had been reached. Antiretrovirals from different classes, used in combination, were exerting a very significant impact on mortality among HIV-infected individuals (Figure 0.1). Clinically, the result was striking. The waiting rooms of HIV clinics were the theaters of astonishing scenes. Patients on the brink of death were putting on weight and regaining stamina. Enthusiasm among patients and clinicians alike was palpable. Psychiatrists too, were enthused. There was a sense that the psychological and neuropsychiatric burden associated with this infection would significantly decrease. Almost 10 years down the road now, it has become clear that the need for psychiatric care has far from decreased. As patients live longer, psychological and psychiatric difficulties negatively impact on quality of life. The efficacy of Highly Active Antiretrovial Therapy (HAART) has a price: strict adherence to a complex medication regimen.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.417 | 0.247 |
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".