Live science in the <i>Valley of the Last Dinosaurs</i> : A public window into the world of paleontology
Bibliographic record
Abstract
ABSTRACT LiveSci in the Valley of the Last Dinosaurs (http://lastdinos.livesci.org/) was a website and social media presence that provided the global online community with unprecedented access to the exciting paleontological research happening in the remote badlands of North Dakota and Montana in the summer of 2016. A collaborative team of researchers, students, and citizen scientists from around the world excavated some of the last dinosaurs that ever walked the Earth, mapped the K/Pg boundary in high resolution, and uncovered fossils that show us how life recovered after the extinction of the dinosaurs. To engage the public in the ongoing process of scientific discovery, dedicated project staff and participating researchers posted videos, photos, blog entries, and social media content nearly every day during the seven-week field season. Researchers and science educators from the Howard Hughes Medical Institute and Denver Museum of Nature & Science, along with collaborators from Brooklyn College, the Smithsonian National Museum of Natural History, Yale Peabody Museum, the Royal Ontario Museum, and the Marmarth Research Foundation, were joined by young scientists and citizen scientist volunteers of all ages. The production team consisted of high school and college interns, public science outreach professionals, and research scientists. To expand the reach of the project, a bilingual intern maintained a parallel Spanish website. Hundreds of thousands of online viewers watched, contributed, and shared these authentic experiences with their communities during the live portion of the project, and many more continue to access the archived website and social media content. This project exemplifies how social media and real-time interaction with scientists have the potential to connect the public to science as it unfolds, removing myths and stereotypes about how science happens and who scientists are. Initiatives such as this one help to create citizens who are more connected to the process of science and who can use that understanding in their lives through more informed decision making.
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 | 0.001 | 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 | 0.023 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 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".