Bibliographic record
Abstract
President's column What is that smell?! As a small boy, after doing the chores on one sunny summer day, I was happy to have a farm to run around on with lots of distractions. Life was grand, and the farm was my oyster. Suddenly, there was this awful smell like rotten eggs wafting from the field. The nearby drilling rig was in operation but something unexpected had happened, and the crew was reacting to the situation. Dad was not sure what to do but was quite concerned about his 5,000 chickens. Chickens, like canaries in coal mines, are quite fragile when it comes to gases in the air. There was no way he could isolate the barn from the smell, so he gathered up the family and, similar to what you would do in a prairie storm, we went to the safest place in the farmhouse to wait it out: the basement. Now, most of you reading this story know exactly what was going on, and—as I am still alive to relay the story—the worst case did not occur. Not a single chicken died, and more importantly, not a single member of the Spady farm family succumbed to the killer hydrogen sulfide gases gathering in the low spots, such as the basement. Not much was ever said about the incident, and I am not sure if Dad ever followed up with the company man on the rig. We were pretty happy to have the novelty of a drilling rig on our farm, and benefited from the surface payments (royalty in Alberta at the time, as now, was generally held by the government). When I grew up it was a normal sight to see large piles of bright yellow sulfur byproduct at nearby gas plants awaiting shipment for agricultural use. This was all part of the new and exciting world of oil and gas that was eclipsing agriculture as the new provider of local jobs. I still drive the farm equipment around that old wellhead when I help with the crop seeding and harvesting. We have co-existed quite nicely for 50 years.
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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 | 0.069 | 0.202 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.021 | 0.012 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.006 | 0.032 |
| Research integrity | 0.011 | 0.021 |
| Insufficient payload (model declined to judge) | 0.040 | 0.014 |
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".