Organic geochemistry of Lake Agassiz sediment cores from southwest Ontario and northern Minnesota in 2023
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
This dataset presents the basic organic geochemistry of Lake Agassiz sediments composing the majority of six long cores from extent lakes in southwestern Ontario and northern Minnesota. Analyses include dry weight density, organic carbon (C) percent (%) , nitrogen (N) percent (%), carbon-13 (13C) (per mil (‰)) and nitrogen-15 (15N) (per mil). These data were used to calculate variable rates of organic carbon accumulation in sediments resulting in part from changes in glacial meltwater inputs to Lake Agassiz. Organic C/N ratios and stable isotope values were also used to infer potential changes in organic matter sources to this lake's sediments over time.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 0.009 |
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