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Record W2202169136 · doi:10.1017/s1473550415000373

Using modern ferruginous habitats to interpret Precambrian banded iron formation deposition

2015· article· en· W2202169136 on OpenAlexaff
Elif Koeksoy, Maximilian Halama, Kurt O. Konhauser, Andreas Kappler

Bibliographic record

VenueInternational Journal of Astrobiology · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeochemistry and Elemental Analysis
Canadian institutionsUniversity of Alberta
FundersDeutsche Forschungsgemeinschaft
KeywordsPrecambrianSedimentary depositional environmentGeologyBanded iron formationBiosphereBiogeochemical cycleEarth scienceGeologic recordDeposition (geology)Natural (archaeology)Lead (geology)GeochemistryPaleontologyEcology

Abstract

fetched live from OpenAlex

Abstract Early Earth processes are typically identified through the study of mineralogical, elemental and isotopic features in the rock record, including Precambrian banded iron formations (BIF). However, post-depositional processes often obscure the primary geochemical signals, making the use of BIF as proxies for paleo-seawater and the paleo-biosphere potentially imprecise. Thus, alternative approaches are required to complement the information gained from the rock record in order to fully understand the distinctive biogeochemical processes on ancient Earth. Simulating these conditions in the laboratory is one approach, but this approach can never fully replicate the complexity of a natural environment. Therefore, finding modern environments with a unique set of geochemical and microbiological characteristics to use as analogues for BIF depositional environments can provide invaluable information. In this review, we provide an overview of the chemical, physical and biological parameters of modern, ferruginous lakes that have been used as analogue BIF environments.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.257

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.271
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations39
Published2015
Admission routes1
Has abstractyes

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