Earthquake Myths and False Information: How to Respond While Avoiding a Mud Fight
Bibliographic record
Abstract
Research Article| September 19, 2018 Earthquake Myths and False Information: How to Respond While Avoiding a Mud Fight Maurice Lamontagne; Maurice Lamontagne aGeological Survey of Canada, Ottawa, Ontario, Canada K1A 0E9, maurice.lamontagne@canada.ca Search for other works by this author on: GSW Google Scholar Christine Goulet Christine Goulet bSouthern California Earthquake Center, University of Southern California, Los Angeles, California 90034 U.S.A., cgoulet@usc.edu Search for other works by this author on: GSW Google Scholar Author and Article Information Maurice Lamontagne aGeological Survey of Canada, Ottawa, Ontario, Canada K1A 0E9, maurice.lamontagne@canada.ca Christine Goulet bSouthern California Earthquake Center, University of Southern California, Los Angeles, California 90034 U.S.A., cgoulet@usc.edu Publisher: Seismological Society of America First Online: 19 Sep 2018 Online Issn: 1938-2057 Print Issn: 0895-0695 © Seismological Society of America Seismological Research Letters (2018) 89 (6): 2411–2412. https://doi.org/10.1785/0220180258 Article history First Online: 19 Sep 2018 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Maurice Lamontagne, Christine Goulet; Earthquake Myths and False Information: How to Respond While Avoiding a Mud Fight. Seismological Research Letters 2018;; 89 (6): 2411–2412. doi: https://doi.org/10.1785/0220180258 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search Earthquake misconceptions and myths are plentiful and can sometimes surprise seismologists (see Table 1). We have all heard poorly documented stories about strange animal behavior before an earthquake, the (usually postearthquake) predictions from psychics about imminent earthquakes, or the enduring myth that people can fall into a chasm when the earth opens up during an earthquake, only to be crushed when it closes again. A web search can reveal numerous examples of these misconceptions, some of them corrected on the U.S. Geological Survey (USGS, 2018) or Earthquake Country Alliance (2011) websites. Interestingly, lessons of the past remind... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.
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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 | 0.011 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.019 | 0.009 |
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".