<i>AJRCCM</i> : 100-Y <scp>ear</scp> A <scp>nniversary</scp> . Sleep-Disordered Breathing: Still the New Kid on the Block
Bibliographic record
Abstract
Sleep-disordered breathing (SDB), of which obstructive sleep apnea (OSA) is by far the most common disorder, is an integral component of respiratory medicine. Although SDB has been described in the literary works of Shakespeare and Charles Dickens (1, 2), only recently has it been formally recognized by the medical community. Indeed, the first clinical characterization of OSA that identified intermittent upper airway obstruction as a major pathogenic mechanism was in the 1960s (3), and the term sleep apnea syndrome was used for the first time in 1973 by Guilleminault and colleagues (4). Continuous positive airway pressure (CPAP) was only first described as an OSA treatment in 1981 by Sullivan and colleagues (5). Therapies such as dental appliances (6), upper airway surgery (7, 8), nasal valves (9), and hypoglossal nerve stimulation (10) are even more recent developments. Even as late as the 1980s, there was skepticism regarding the importance of the disease, with a letter suggesting that OSA was rare (11). How times have changed! During the last 30 years, there has been an avalanche of research that has investigated all aspects of SDB, including the pathogenesis, physiology, consequences, genetics, and epidemiology of SDB. These advances are a testament to the dedication, vision, and hard work of countless investigators.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.698 | 0.595 |
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".