Evaluation of aeolian dust records obtained from Polar Ice Cores
Bibliographic record
Abstract
When an ice core sample is analysed for its aeolian dust content, it is melted and the particles detected \nare suspended in water. Consequently, dust measurement techniques employed in the ice core \ncommunity differ from those used for in-situ studies of airborne dust. \nMethods commonly used to classify insolubles suspended in a liquid are either based on the particles’ \ninteraction with light or on the detection of resistive pulses by means of Coulter counting. Data sets \nobtained with Coulter counters are widely accepted as references and other techniques are judged \nagainst their ability to reproduce these. \nUnfortunately, optically acquired ice core dust records were found to differ. By analyzing two \nsections of the NEEM dust record, two different evaluation procedures are discussed before a third \nprotocol is proposed. It is found that relative changes in the archived dust load can be reproduced, \nwhile the simultaneous attainment of absolute concentrations or changes in the grain size frequency \nhistograms in high resolution remains difficult.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".