Limiting LNG: Public Perception Hinders the Role of Liquefied Natural Gas Domestically
Bibliographic record
Abstract
Natural gas serves as an important alternative to higher carbon emitting fuels which meet our needs for heating, cooking, transportation and electricity. The versatility and high BTU value of natural gas is well appreciated and pipelines crossing our country have been in service for some time. The pipelines that link domestic and Canadian sources do not meet all of our demand and we are augmented by liquefied natural gas (LNG) import terminals. The pipelines draw little concern from the public while terminals are viewed very differently. Terminals have imported (and exported) LNG safely since 1969 but public perception is converse to the strong industry record in this regard. Criticisms center around security threats and environmental hazards associated with the ships and terminals. Unfortunately, the risks are not being assessed on probability and consequence. Meanwhile, LNG fits much more prominently into the energy strategy of several developed nations. A review of Japanese energy strategy demonstrates that public perception has been paramount in allowing terminals to be cited in high density urban areas close to the population being served. Important recent studies into hazard and consequence behind LNG risks are also reviewed.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".