NCAR ACOM Manitou SPIFFY2015 Campaign Data. Version 1.0
Bibliographic record
Abstract
This dataset contains the SPIFFY2015 campaign data collected by NSF NCAR Atmospheric Chemistry Observations & Modeling (ACOM) for the Manitou Experimental Forest Observatory (MEFO) between 2008 and 2016. The complete Manitou data archive contains data in a variety of formats (e.g., ASCII, ICARTT, JPEG) from the following field campaigns: Manitou2008, Manitou2009, Manitou2011, Manitou2014, Manitou2015, Manitou2016, SPIFFY2015, SPIFFY2016, Beachon-SRM (2008), 2010 Beachon ROCS, 2011 Beachon-RoMBAS, and 2015 Rx Burn. No data was collected for the 2016 CSU Cont. project. This dataset contains the data from the SPIFFY2015 campaign. The data are from the Manitou Experimental Forest Observatory (MEFO) that was established in 2008, in an area representative of a middle-elevation (~2000-2500 m ASL). It is a semi-arid, ponderosa pine ecosystem that is common throughout the Rocky Mountain West. The station location is at 39.1006 degrees North, 105.0942 degrees West and at an elevation of 7700 feet ASL (2347 m). The chemistry tower at MEFO is a walk up type with height of 28m and there were 4 mobile laboratories with 160 Ft2 (14.9m2) space. A variety of data (e.g., meteorological, trace gases, Flux, CIMS) is contained in the Manitou data archive and it varies by year and campaign. See the dataset readme files for more information on all data collected. Learn more on the MANITOU project page at eol.ucar.edu/manitou.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.028 |
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".