The Archean Nickel Famine Revisited
Bibliographic record
Abstract
Iron formations (IF) preserve a history of Precambrian oceanic elemental abundance that can be exploited to examine nutrient limitations on early biological productivity. However, in order for IF to be employed as paleomarine proxies, lumped-process distribution coefficients for the element of interest must be experimentally determined or assumed. This necessitates consideration of bulk ocean chemistry and which authigenic ferric iron minerals controlled the sorption reactions. It also requires an assessment of metal mobilization reactions that might have occurred in the water column during particle descent and during post-depositional burial. Here, we summarize recent developments pertaining to the interpretation and fidelity of the IF record in reconstructions of oceanic trace element evolution. Using an updated compilation, we reexamine and validate temporal trends previously reported for the nickel content in IF (see Konhauser et al., 2009 ). Finally, we reevaluate the consequences of methanogen Ni starvation in the context of evolving views of the Archean ocean-climate system and how the Ni famine may have ultimately facilitated the rise in atmospheric oxygen.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".