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Record W6929884167 · doi:10.5066/p9m6eckk

Ratios of strontium to calcium measured in pectoral fin rays of lake sturgeon (Acipenser fulvescens) captured in the lakes and rivers of Namakan Reservoir, Minnesota, United States and Ontario, Canada, 2007-15

2019· dataset· en· W6929884167 on OpenAlexaboutno aff

Bibliographic record

VenueUSGS DOI Tool Production Environment · 2019
Typedataset
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
Fundersnot available
KeywordsTransectStrontiumFish finSturgeonFinAblation

Abstract

fetched live from OpenAlex

The U.S. Geological Survey, Voyageurs National Park, South Dakota State University, and Missouri Department of Conservation conducted a cooperative study to measure ratios of strontium to calcium (Sr:Ca) in cross sections of pectoral fin rays obtained from lake sturgeon (Acipenser fulvescens) captured in lakes and rivers of Namakan Reservoir in Minnesota and Ontario. We measured Sr:Ca ratios in cross sections of 37 pectoral fin rays collected from 10 locations (5 rivers and 5 lakes) in Namakan Reservoir as part of a larger study to investigate whether relations between Sr:Ca in water and pectoral fin rays were significant and useful for determining migratory histories of lake sturgeon in Namakan Reservoir. Pectoral fin rays were removed nonlethally at the time of capture from lake sturgeon captured during surveys collected from 2007-09. Cross sections of collected pectoral fin rays were analyzed using laser ablation inductively-coupled plasma mass spectrometry at the University of Massachusetts at Amherst. Laser ablation transects started in the center of the fin ray cross section near the origin, which represents growth from birth through the first year of life. Laser ablation transects advanced outward toward the edge of the fin ray cross section, which represents the most recent growth of the lake sturgeon. Laser ablation analyses occurred November 2-6, 2015. Photographs of ablated pectoral fin ray cross sections were taken using a digital camera mounted to a microscope.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.256
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.258
Teacher spread0.229 · 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 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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