USWRP Workshop on Air Quality Forecasting
Bibliographic record
Abstract
Vaisala, Inc., Boulder, ColoradoUniversity of Michigan, Ann Arbor, MichiganMeteorological Service Canada, Dartmouth, Nova Scotia, CanadaUniversidad Nacional Autónoma de México, México DF, MéxicoUniversity of Iowa, Iowa City, IowaNational Oceanic and Atmospheric Administration, National Weather Service, Silver Spring, MarylandPacific Northwest National Laboratory, Richland, WashingtonSonoma Technology, Inc., Petaluma, CaliforniaIndiana University, Bloomington, IndianaPanorama Pathways, Boulder, ColoradoNational Oceanic and Atmospheric Administration, Oceanic and Atmospheric Research, Boulder, ColoradoAtmospheric and Environmental Research, Inc., San Ramon, California*CURRENT AFFILIATION: North Carolina State University, Raleigh, North CarolinaCORRESPONDING AUTHOR: Walter F. Dabberdt, Vaisala Inc., P.O. Box 3659, Boulder, CO 80307-3659, E-mail: walter.dabberdt@vaisala.com
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".