Carbon monoxide poisoning associated with blasting operations close to underground enclosed spaces. Part 1. CO production and migration mechanisms
Bibliographic record
Abstract
Explosives used for blasting operations in civil engineering works can generate large volumes of carbon monoxide (CO). The production of 1024 L of CO per kilogram of explosives blasted is theoretically possible. CO can migrate a considerable distance in the fractured rock of the blasted areas and then infiltrate closed spaces (sewage systems, manholes, basements of houses). In the Province of Quebec, in the last 10 years, seven people were poisoned by CO in their houses to the extent that they had to be treated in a hyperbaric chamber. Underground conduits broken by blasting, filling around underground conduits in road or house trenches, or fractured rock created by blasts between houses or between a house and a road are the different CO pathways identified in the Quebec incidents. Field tests done by our group show that (i) the structural geology of the rock formation (schistosity, family of joints and fractures) controls the direction and extent of gas migration in fractures generated by blasts; (ii) the confinement of the rock can affect the quantity of gas migrating in the fractured rock; (iii) significant concentrations of CO may persist in the fractured rock 7 days after a blast; (iv) advection is the initial mechanism of CO migration immediately after a blast, and the distance of migration varied from 8 m in the fractured rock to 20 m in the fills of a road trench; and (v) further CO migration by diffusion up to 15 m in the induced fractures and 30 m in fills may occur in the 3 days following a blast.Key words: carbon monoxide, blasting, poisoning, enclosed spaces, gas migration, house.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".