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Record W6926472901 · doi:10.21966/jxrd-8g95

Carbon and nitrogen stable isotope ratios and elemental composition of specimens from the pelagic food web collected during the 2019 International Year of the Salmon expedition to the Gulf of Alaska

2019· dataset· en· W6926472901 on OpenAlexaff

Bibliographic record

VenueHakai Institute · 2019
Typedataset
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsZooplanktonPelagic zoneNitrogenSeawaterFood webStable isotope ratioCarbon fibersOn boardSieve (category theory)

Abstract

fetched live from OpenAlex

All samples were collected on board of the chartered R/V Professor Kaganovsky between February and March 2019 during the winter expedition of the International Year of the Salmon project to the Gulf of Alaska, North Pacific Ocean. Samples of Particulate Organic Matter (POM) were obtained by filtering approximately 2 L of water onto pre-combusted 25 mm GF/F filters with a vacuum pump. Water samples were collected at every station from 5m depth using Niskin bottles. Two replicates were filtered per station, one subsample was acidified by immersion in 1M HCl for 30 seconds. After acidification, the sample was rinsed with 0.7 μm filtered seawater and dried by applying vacuum pressure to the filter. Each filter was transferred to its own aluminum foil envelope and stored at -20oC. Zooplankton samples were collected with a Bongo net (50 cm mouth diameter and 236 µm mesh) hauled vertically from 250 m depth. The zooplankton sample collected at each station was size fractionated using a sieve stack with 4 mm, 2 mm, 1 mm, 0.5 mm and 0.25 mm mesh sizes, and then frozen at -40°C. Samples of salmon, squids, jellyfish, myctophids and other fishes were obtained using a surface trawl (~120 m2, 30m deep x 40m wide) deployed at each station and towed at 4-5 knots for one hour. All organisms caught in the trawl were identified to the lowest practical taxon (species except for some invertebrates), enumerated, and measured (length [total, fork, mantle, or bell diameter as appropriate] to the nearest 1 mm, weight to the nearest 1 g). For salmonids, a 2x2 cm piece of muscle tissue was collected from above the lateral line and in front of the dorsal fin and stored at -40°C. For large non-salmonid fish, a muscle sample was collected in the same way as for salmonids samples. A 2x2 cm piece of muscle from the anterior dorsal margin of the mantle was collected from squids, and jellyfish were collected either whole or a piece in the case of large specimens. For micronekton species, either a piece of muscle was sampled (e.g., myctophids posterior region; squids’ mantle) or the specimen was analysed whole (e.g., krill, small jellyfish). All samples were stored frozen at -20○C. Samples were then processed in the laboratory at the University of British Columbia. POM Filters were oven dried at 50°C and later encapsulated for isotopic analysis. POM ẟ13C values are reported from the set of acidified samples, while ẟ15N are reported from non-acidified samples. Animal samples were either oven dried at 50°C (zooplankton, squids, myctophids and non-salmonid fishes) or freeze-dried (salmon and jellyfish), and then homogenized to a fine powder using mortar and pestle. Approximately 1 mg of each sample was encapsulated in tin caps and sent for carbon and nitrogen analysis at the UC Davis stable isotope facility (Davis, CA, USA). Tissue samples were analysed using an elemental analyser (PDZ Europa ANCA-GSL) interfaced to an isotope ratio mass spectrometer (PDZ Europa 20-20, Sercon Ltd., Cheshire, UK). Details on analytical procedure are provided in the supplementary materials 1. The data reported includes each sample ẟ13C (raw and lipid corrected, see supplementary material 1 and 2), total C content (mg), ẟ15N, total N content (mg), CN ratios, calculated trophic positions (see supplementary material 3), and salmon condition factor (supplementary material 4), in addition to the metadata associated with each sample (e.g., coordinates of oceanographic station and bottom depth where specimens were collected, etc.).

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.294

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 head0.011
GPT teacher head0.221
Teacher spread0.210 · 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 designNot applicable
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

Citations0
Published2019
Admission routes1
Has abstractyes

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