RADIv1: a non-steady-state early diagenetic model for ocean sediments in Julia and MATLAB/GNU Octave
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
Abstract. We introduce a time-dependent, one-dimensional model of early diagenesis that we term RADI, an acronym accounting for the main processes included in the model: chemical reactions, advection, molecular and bio-diffusion, and bio-irrigation. RADI is targeted for study of deep-sea sediments, in particular those containing calcium carbonates (CaCO3). RADI combines CaCO3 dissolution driven by organic matter degradation with a diffusive boundary layer and integrates state-of-the-art parameterizations of CaCO3 dissolution kinetics in seawater, thus serving as a link between mechanistic surface reaction modeling and global-scale biogeochemical models. RADI also includes CaCO3 precipitation, providing a continuum between CaCO3 dissolution and precipitation. RADI integrates components rather than individual chemical species for accessibility and is straightforward to compare against measurements. RADI is the first diagenetic model implemented in Julia, a high-performance programming language that is free and open source, and it is also available in MATLAB/GNU Octave. Here, we first describe the scientific background behind RADI and its implementations. Following this, we evaluate its performance in three selected locations and explore other potential applications, such as the influence of tides and seasonality on early diagenesis in the deep ocean. RADI is a powerful tool to study the time-transient and steady-state response of the sedimentary system to environmental perturbation, such as deep-sea mining, deoxygenation, or acidification events.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it