Bibliographic record
Abstract
Ontario, Canada, covers an area of 412,582 square miles, extending 1,000 miles from east to west and 1,500 miles from south to north. The population of Ontario at the time of the 1961 census was 6,236,092: 78 per cent were born in Canada; 22 per cent were born elsewhere. The population included 47,862 North American Indians who live, generally speaking, at a lower socioeconomic level. The northern part of the province is sparsely populated, by far the larger proportion of the population being found in the southern and eastern regions, where most of the agriculture and industry are located. About 25 per cent of the population is concentrated in the metropolitan Toronto area. Ontario is the richest of Canada's provinces and contributes 41 per cent of the annual gross national product. In terms of material wealth, the development of disease control, the availability of drugs and hospital facilities, and the general standard of living, Ontario has been fortunate in comparison with many parts of the world. In this paper current aspects of tuberculosis in Ontario will be discussed in terms of: ( 1) the distribution and significance of tuberculin sensitivity; and (2) the incidence of active tuberculous disease (or morbidity) . The mortality from tuberculosis in Ontario is fortunately too low (2.6 per 100,000 in 1962) to provide a helpful epidemiologic index.
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 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".