Bibliographic record
Abstract
This dataset holds Level 1B (L1B) radiance data collected by the AVIRIS-Classic instrument near Prince Albert, Saskatchewan, Canada, on August 14, 1996. This imagery was acquired for the Boreal Ecosystem-Atmosphere Study (BOREAS) project in the boreal forests of central Canada. BOREAS focused on improving the understanding of exchanges of radiative energy, sensible heat, water, CO2 and trace gases between the boreal forest and the lower atmosphere. NASA's AVIRIS-Classic is a pushbroom spectral mapping system with high signal-to-noise ratio (SNR), designed and toleranced for high performance spectroscopy. AVIRIS-Classic measures reflected radiance in 224 contiguous bands at approximately 10-nm intervals in the Visible to Shortwave Infrared (VSWIR) spectral range from 400-2500 nm. The AVIRIS-Classic sensor has a 1 milliradian instantaneous field of view, providing altitude dependent ground sampling distances from 20 m to sub meter range. For these data, AVIRIS-Classic was deployed on NASA's ER-2 high altitude aircraft. These spectra are acquired as images with 20-meter spatial resolution, 11 km swath width, and flight lines up to 800 km in length. The measurements are spectrally, radiometrically, and geometrically calibrated. There are seven flight lines subdivided into 66 scenes. The dataset includes the radiance imagery cube for each scene along with calibration and navigation information. The radiance data are in instrument coordinates, georeferenced by center of each scan line, and provided in a binary file. Metadata are included in a mixture of binary and text file formats.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".