Bibliographic record
Abstract
This study began with a serendipitous observation.Several years ago, when I first examined the Alberta Energy Regulator's spill data, I noticed a curious property.If one cubic metre was spilled of, say, crude oil, one cubic metre was recovered; if five cubic metres were spilled, five cubic metres were recovered, and so on.Certainly, that can happen by chance.But tens of thousands of spills reporting an exact duplication of volumes spilled and volumes recovered cannot happen in the real world.I graphed spill volume against recovery volume.It was a straight-line 1:1 relationship.In short, the spill recoveries were too good to be true.At that point, I smelled smoke and went looking for the fire.If the reported spill recoveries were not scientifically credible, serious questions arose.Did it mean that undetermined volumes of spilled materials remain on the landscape?Were industry-reported spill and recovery volumes accurate?After cleanup operations, was there evidence of residual contamination and biological effects?Were any of the regulator's environmental data on spills supported by science?Was the regulator protecting the environment?Those questions prompted discussions with Keepers of the Water Council, a nonprofit citizens' water advocacy and conservation group.Keepers, along with the Dene Tha, a First Nation directly affected by fossil fuel industry spills, asked me to examine spills data in concert with a field study.I completed the initial phase of the study, focused in northwestern Alberta, in late 2016.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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 teacher head, 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".