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Record W2948805856 · doi:10.1139/facets-2018-0027

Seasonal patterns in deep acoustic backscatter layers near vent plumes in the northeastern Pacific Ocean

2019· article· en· W2948805856 on OpenAlexaffvenue
Brenda J. Burd, Richard E. Thomson

Bibliographic record

VenueFACETS · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsNorth Pacific Marine Science Organization
Fundersnot available
KeywordsPlumeGeologyOceanographyRidgeSeafloor spreadingZooplanktonHydrothermal ventWater columnSeabedDeep seaPaleontologyHydrothermal circulationGeographyMeteorology

Abstract

fetched live from OpenAlex

We used moored 75 kHz acoustic Doppler current profilers (ADCPs) to examine seasonal cycles in zooplankton deep scattering layers (DSLs) observed below 1300 m depth at Endeavour Ridge hydrothermal vents. DSLs are present year-round in the lower water column near vent plumes. Temporal variations suggest passive, flow-induced displacements superimposed on migratory movements. Although the strongest DSLs are shallower than the neutrally buoyant plumes (1900–2100 m), anomalies also occur at and below plume depth. Upward movement from plume depth in the main DSL is evident in late summer/fall, resulting in shallower DSLs in winter, consistent with the timing of adult diapause/reproduction in upper-ocean migratory copepods. Movement from the upper ocean to plume depth coincides with pre-adult migration to greater depths in spring. Synchronous 20–40 d cycles in DSLs may account for patchiness in space and time of above-plume zooplankton layers observed in summer during previous net-sampling surveys, and suggests lateral and vertical migratory movements to counter current drift away from plume-derived food sources. Persistent near-bottom DSLs move vertically between the spreading plume and seafloor. Historical net data suggests that these are deep, resident fauna. Unlike upper ocean fauna, they seem to be advected considerable distances from the ridge axis, where they are evident as remnant scattering layers.

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 score0.025
Threshold uncertainty score0.999

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)0.0020.001

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 head0.006
GPT teacher head0.189
Teacher spread0.183 · 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
Published2019
Admission routes2
Has abstractyes

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