WINTRE-MIX: NRC Convair 580 Aerosol Data. Version 2.0
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A suite of aerosol instruments were integrated on the NRC Convair-580 aircraft and operated in the WINTRE-MIX flight campaign, between February and March, 2022. The list includes a Condensation Particle Counter (CPC), Ultra-High Sensitivity Aerosol Spectrometer (UHSAS), Single Particle Soot Photometer (SP2), and a Cloud Condensation Nuclei counter (CCNc), which were installed in the aircraft cabin to sample via an isokinetic inlet installed on top of the fuselage. In addition, NRC wing tip mounted UHSAS was installed and sampled throughout the whole campaign. Due to the nature of Intensive Operational Periods (IOP)s, most of the flight time in the domain was spent in-cloud or in precipitation with the associated risk of flooding the cabin aerosol instruments, which led to the suspension of aerosol sampling. To address this issue, towards the latter portion of the campaign, starting from IOP7, a Counter-flow Virtual Impactor (CVI) inlet system was integrated on the fuselage starboard side window, for the first time. The CVI inlet allowed in-cloud sampling of the residual aerosol (remaining core after evaporation of the hydrometeors above a selected cut-off diameter). A cabin inlet-switching mechanism was designed for the campaign, allowing to switch between the sampling lines of an isokinetic inlet and a CVI inlet. The collected data includes information for in-cloud and clear-air aerosol particle size distributions, CCN activation properties, activated fraction, vertical profiles, and limited information about composition (Black Carbon vs. light scattering aerosol). The CVI was never tested on this aircraft before WINTRE-MIX. Therefore, the quality of data requires further review and validation. Please see the readme file for this dataset for more information.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.053 | 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 it