Response to: Low back pain: doesn't work matter at all?
Bibliographic record
Abstract
We wish to thank Kuijer et al. for their continued interest in our research and their response to our systematic review which we prepared in recognition of the role played by occupational health physicians in managing low back pain (LBP) and adjudicating claims for injured workers [1]. Our review identified, appraised, summarized and synthesized the scientific evidence available to support a causal relationship between occupational physical activities (e.g. bending, lifting) and LBP. The framework for our analysis included various Bradford Hill criteria for causation [2], which were applied to individual studies (e.g. association) and groups of studies (e.g. consistency) as appropriate. Within these criteria, we determined the level of scientific evidence available (e.g. moderate evidence of positive association) in order to assess the presence of causal relationships between specific occupational physical activities and LBP. While our analysis found evidence supporting some aspects of causation (e.g. association, dose–response) for some physical activities (e.g. bending, twisting) and LBP, its findings were mixed. Undoubtedly, the aetiology of LBP is multifactorial [3]. A corollary to this notion is that no single factor is likely to cause LBP. Since our reviews attempted to isolate the causal effects of occupational physical activities, our conclusions that many activities were likely not independently causal of LBP are consistent with a multifactorial hypothesis. It should come as no surprise that any study focused on the role of isolated factors, whether physical, psychosocial, occupational, genetic, or other, will likely conclude that the factor studied is not sufficient, when acting alone, to cause LBP in workers.
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 | 0.009 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.025 | 0.015 |
| Insufficient payload (model declined to judge) | 0.046 | 0.015 |
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".