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Record W4285410973 · doi:10.3133/pp1870

Marine minerals in Alaska — A review of coastal and deep-ocean regions

2022· article· en· W4285410973 on OpenAlexaboutno aff
Amy Gartman, Kira Mizell, Douglas C. Kreiner

Bibliographic record

VenueUSGS professional paper · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeochemistry and Elemental Analysis
Canadian institutionsnot available
FundersBureau of Ocean Energy ManagementU.S. Geological SurveyUniversity of California, Santa CruzU.S. Department of the Interior
KeywordsGeologySeamountOceanographyAbyssal plainBayGeochemistryHydrothermal ventContinental shelfSeafloor spreadingEarth scienceStructural basinPaleontologyHydrothermal circulation

Abstract

fetched live from OpenAlex

First posted July 14, 2022 For additional information, contact: Pacific Coastal and Marine Science CenterU.S. Geological Survey2885 Mission St.Santa Cruz, CA 95060 Minerals occurring in marine environments span the globe and encompass a broad range of mineral categories, forming within varied geologic and oceanographic settings. They occur in coastal regions, either from the continuation or mechanical reworking of terrestrial mineralization, as well as in the deep ocean, from diagenetic, hydrogenetic, and hydrothermal processes. The oceans cover most of the Earth's surface and as a result, any inventory of global resources is incomplete without the inclusion of marine minerals. This study by the U.S. Geological Survey reviews current knowledge regarding deep-ocean and coastal marine minerals within the marine areas surrounding Alaska, including the Alaska Outer Continental Shelf (OCS). For the purposes of this study, we have divided these areas in to eight regions: (1) Gulf of Alaska seamounts, (2) Chukchi Borderland, (3) Canada Basin, (4) Aleutian Arc, (5) Seward Peninsula, (6) Goodnews Bay, (7) Bristol Bay and Alaska Peninsula, and (8) southern and southeastern Alaska. The Alaska OCS encompasses several areas broadly conducive to marine mineral formation, including extensional basins resulting from an active subduction zone where massive sulfide deposits may form, deep abyssal plains with conditions that may lead to manganese nodule formation, seamounts that can provide substrate for the growth of ferromanganese crusts, and erosional settings and submerged continental crust where placer deposits are found. For deep-ocean hydrothermal minerals and manganese nodules, the Alaska OCS contains prospective regions, including the Canada Basin and the Aleutian Arc; however, no such minerals have yet been identified. We explore the probability that these minerals occur based on reviews of existing geologic and oceanographic data within the relevant sections. In regions far from shore data are limited. Deep-ocean ferromanganese crusts are known to occur in two regions: (1) the Gulf of Alaska seamounts and (2) the Chukchi Borderland in the Arctic Ocean. Limited sampling has occurred in both regions, and along the Chukchi Borderland the sampling was outside of the OCS and the U.S. Exclusive Economic Zone. Data relevant to coastal minerals is more extensive, and in some places fairly systematic sampling was conducted. Several nearshore placer deposits have been exploited for decades; however, the potential for nearshore extension of terrestrial ore deposits is less well considered. This contribution considers the state of knowledge regarding marine mineral occurrences within the Alaska regions and identifies the data gaps in order to help inform future marine mineral related research efforts around Alaska.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.975

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)0.0260.000

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 head0.009
GPT teacher head0.226
Teacher spread0.217 · 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.

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

Citations8
Published2022
Admission routes1
Has abstractyes

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