Annie Pootoogook. Mendel Art Gallery, September 19, 2008 - January 4, 2009Mendel Art Gallery, September 19, 2008 - January 4, 2009
Bibliographic record
Abstract
Assessing the effect of novel pharmaceutical treatments on the quality of life (QoL) of a patient, or group of patients, has been approached in numerous ways over the last 20 years. Techniques as diverse as single questions to multidimensional scales requiring trained assessors to devote several hours to each assessment; from generic questions about how life might have changed to specific issues such as the ability to use a toothbrush. In the pharmaceutical industry, the emphasis is on the registration of a product with national licensing bodies. Each body has tended to see the issue from a different perspective, which has driven study designs to be different in different countries; even different over time within one country. This paper emphasises the basic statistical steps necessary to ensure that a measure of QoL is appropriately recorded, while retaining sufficient flexibility to support the registration in several countries. Aspects about possible study design are included to assist with developing some simple concepts about analysing and then interpreting the results. It is not the intention of the paper to provide the answer, merely to provide the tools to develop the answer robustly. Put briefly, with the right approach generic solutions are feasible and these solutions will have greater utility. The challenge is to recognise exactly what QoL is, and not to deviate from it.
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.
How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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; both teacher heads agree on what is shown here.
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".