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Record W3129209618

Modern calibration of biomarkers in the marine channels of the Canadian Arctic Archipelago using the PIP25 approach

2017· article· en· W3129209618 on OpenAlexaffabout
Craig Neilson, Anna J. Pieńkowski

Bibliographic record

VenueURSCA Proceedings · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsMacEwan University
Fundersnot available
KeywordsSea iceOceanographyGeologyAlgaeArcticArctic ice packPhytoplanktonEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

Two lipid biomarkers, IP25 (a highly branched isoprenoid hydrocarbon; an ice proxy containing 25 carbon atom skeleton) and brassicasterol (phytoplankton derived biomarker), accumulate and become preserved in the marine sediments on the seafloor. IP25 is produced by sea ice algae (marine diatoms) while brassicasterol is produced by a suite of open-water algae (dinoflagellates, diatoms), allowing for determination of sea surface conditions in relation to sea ice conditions during accumulation. Absence of IP25 in marine sediments can indicate permanent sea ice coverage or absence of sea ice completely. High IP25 concentrations reveal sea ice conditions by which sea ice algae can thrive. High brassicasterol concentrations are an indicator of ice free surface conditions, whereas, an absence of brassicasterol would suggest sea ice coverage. Following extraction and quantification via Gas Chromatography Mass Spectroscopy, their respective concentrations can be related to each other in a ratio known as PIP25 (Phytoplankton-IP25 index) to reconstruct specific sea ice conditions (marginal ice zone, perennial ice cover, ice free, etc.). The PIP25 approach allows for currently accumulating IP25 and brassicasterol to be related to observed modern sea ice conditions, therefore providing a regionally appropriate calibration for the study of past conditions in the geological record. This study focuses on the modern calibration of these biomarkers in the marine channels of the Canadian Arctic Archipelago. * Indicates faculty mentor.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.025
GPT teacher head0.219
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2017
Admission routes2
Has abstractyes

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Same venueURSCA ProceedingsSame topicArctic and Antarctic ice dynamicsFrench-language works237,207