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Record W4294237906 · doi:10.1038/s41467-022-32815-x

Marine phosphate availability and the chemical origins of life on Earth

2022· article· en· W4294237906 on OpenAlexfundno aff
Matthew P. Brady, Rosalie Tostevin, Nicholas J. Tosca

Bibliographic record

VenueNature Communications · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrigins and Evolution of Life
Canadian institutionsnot available
FundersMedical Research CouncilLeverhulme TrustUniversity of CalgaryCalifornia Institute of Technology
KeywordsPhosphateSeawaterHadeanAnoxic watersEarly EarthSolubilityAbiogenesisEnvironmental chemistryPhosphorusAquatic ecosystemExtraterrestrial lifeChemistryPhosphate mineralsArcheanApatiteEnvironmental scienceEcologyAstrobiologyMineralogyGeologyBiologyGeochemistryBiochemistry

Abstract

fetched live from OpenAlex

Abstract Prebiotic systems chemistry suggests that high phosphate concentrations were necessary to synthesise molecular building blocks and sustain primitive cellular systems. However, current understanding of mineral solubility predicts negligible phosphate concentrations for most natural waters, yet the role of Fe 2+ , ubiquitous on early Earth, is poorly quantified. Here we determine the solubility of Fe(II)-phosphate in synthetic seawater as a function of pH and ionic strength, integrate these observations into a thermodynamic model that predicts phosphate concentrations across a range of aquatic conditions, and validate these predictions against modern anoxic sediment pore waters. Experiments and models show that Fe 2+ significantly increases the solubility of all phosphate minerals in anoxic systems, suggesting that Hadean and Archean seawater featured phosphate concentrations ~10 3 –10 4 times higher than currently estimated. This suggests that seawater readily met the phosphorus requirements of emergent cellular systems and early microbial life, perhaps fueling primary production during the advent of oxygenic photosynthesis.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.259
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations51
Published2022
Admission routes1
Has abstractyes

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