Ground-penetrating radar and shallow firn cores from Devon Ice Cap, Canadian Arctic
Bibliographic record
Abstract
GPR data and firn cores were collected over Devon Ice Cap, Canadian Arctic in May 2015. ----------------------------------------------------------------- Firn cores Six ~11 m long firn cores were drilled using a Kovacs drill (9 cm diameter) along the GPR profiles. Pictures were taken of the firn cores, which were subsequently used to log the firn facies. From each core, three sections at different depths that did not include ice layers were weighted with a digital scale and used to calculate the firn density. At each firn core location, the snow depth was recorded, as well as at an additional location where a snow pit was dug (SPB1). DIC_firn_cores_2015_density.xlsx: Firn core density measurements. Three measurements were taken from each core, using ice-free sections. DIC_firn_cores_2015_stratigraphy.xlsx: Firn stratigraphy for each core location, derived from the firn core pictures. F stands for firn, I for ice layer, and P for percolation pipe/feature (ice in the firn core that does not present as an ice layer throughout the core diameter). DIC_snowdepth_2015.xlsx: Snow depth measurements at each core location. Firn_core_pictures.zip: Pictures of the firn cores taken with infrared and visible light cameras. ----------------------------------------------------------------- GPR data GPR data were collected with a PulseEKKO Noggin radar (Sensors & Software Inc.) with 500 MHz center frequency antennae (i.e., 0.6 m wavelength). The antennae were mounted on a plastic sled towed by snowmobile, generating a data set sampled every ~0.4 m along track. Positioning was obtained with a Leica Geosystems GPS system providing a 25 cm RMS accuracy. Processing of the GPR data was performed in Matlab and included dewow filtering, time-zero shift, background removal, Butterworth band-pass filtering and the application of a gain function. PulseEkko_RawData: Folder containing the raw PulseEKKO GPR and GPS files. PulseEkko_ProcessedData: Contains the processed GPR data as .mat files. Description of the data files can be found in ProcessedData_readme.txt.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".