16 Good Golly, Why Moly? THE STABLE ISOTOPE GEOCHEMISTRY OF MOLYBDENUM
Bibliographic record
Abstract
The subsequent ~15 years of research yielded an emphatic answer of "yes", centered in particular on paleoceanographic applications, but also extending to the solid Earth geosciences and other areas.This review provides an overview of this maturing isotope system, with an emphasis on paleoredox applications that dominate the literature.It is intended as an update of the reviews written when the Mo isotope system was still emerging (Anbar, 2004;Anbar and Rouxel, 2007).Section 2 covers analytical methodology.Sections 3 and 4 provide the necessary context for Mo isotope studies by reviewing Mo biogeochemistry and Mo isotope fractionation factors.Section 5 explores Mo isotope variations in meteorites and Earth reservoirs, with an emphasis on the large database for marine sediments.In the context of modern observations of the ocean Mo cycle, the use of Mo isotopes as a local and global ocean paleoredox proxy is synthesized in section 6.In section 7, we explore the rapidly growing application of Mo isotopes to ore deposits, oil, and anthropogenic tracing, areas that are expected to see strong growth in the near future. ANALYTICAL CONSIDERATIONS Data ReportingMolybdenum stable isotope fractionation is conventionally reported in δ 98 Mo notation as parts per thousand deviation of the 98 Mo/ 95 Mo ratio relative to a universal reference material.Older data were reported relative to in-house reference materials thought to be identical in composition.However, the analytical precision has improved since then and a common reference material is necessary because various in-house reference materials now differ by up to 0.37‰ (Goldberg et al., 2013).The Mo standard solution, NIST-SRM-3134, has been defined as an international reference material, and is assigned a distinct δ 98 Mo value of 0.25‰ to account for its offset from the most common in-house standards used previously (Nägler et al., 2014).On this scale, the Mo isotope composition of samples can be calculated as follows:δ 98 Mo = [( 98 Mo/ 95 Mo)sample /( 98 Mo/ 95 Mo)NIST-SRM-3134) -1] × 1000 + 0.25 [‰] If the δ 98 Mo of the in-house reference material relative to the NIST-SRM-3134 standard is known, then it is possible to re-normalize the Mo isotope composition of a sample from the inhouse reference scale to the NIST-SRM-3134 scale.If the isotopic offset between the in-house and NIST-SRM-3134 standards is not known, it is still possible to convert between the two scales by measuring a well-known secondary standard such as seawater (e.g., IAPSO) or the USGS rock reference material SDO-1, which has δ 98 Mo = 1.05 ± 0.14‰ (2σ = 2 standard deviations) on the NIST-SRM-3134 scale (Goldberg et al. 2013;Nägler et al., 2014).
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How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.032 | 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 teacher head, 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".