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Record W6959191083 · doi:10.1021/es502086e.s001

What’s\nin an EEM? Molecular Signatures Associated\nwith Dissolved Organic Fluorescence in Boreal Canada

2016· article· en· W6959191083 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsnot available
Fundersnot available
KeywordsDissolved organic carbonBorealBiogeochemical cycleFluorescenceMass spectrometryFluorescence spectrometryMatrix (chemical analysis)Analytical Chemistry (journal)Resolution (logic)

Abstract

fetched live from OpenAlex

Dissolved\norganic matter (DOM) is a master variable in aquatic\nsystems. Modern fluorescence techniques couple measurements of excitation\nemission matrix (EEM) spectra and parallel factor analysis (PARAFAC)\nto determine fluorescent DOM (FDOM) components and DOM quality. However,\nthe molecular signatures associated with PARAFAC components are poorly\ndefined. In the current study we characterized river water samples\nfrom boreal Québec, Canada, using EEM/PARAFAC analysis and\nultrahigh resolution mass spectrometry (FTICR-MS). Spearman’s\ncorrelation of FTICR-MS peak and PARAFAC component relative intensities\ndetermined the molecular families associated with 6 PARAFAC components.\nMolecular families associated with PARAFAC components numbered from\n39 to 572 FTICR-MS derived elemental formulas. Detailed molecular\nproperties for each of the classical humic- and protein-like FDOM\ncomponents are presented. FTICR-MS formulas assigned to PARAFAC components\nrepresented 39% of the total number of formulas identified and 59%\nof total FTICR-MS peak intensities, and included significant numbers\ncompounds that are highly unlikely to fluoresce. Thus, fluorescence\nmeasurements offer insight into the biogeochemical cycling of a large\nproportion of the DOM pool, including a broad suite of unseen molecules\nthat apparently follow the same gradients as FDOM in the environment.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score0.981

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)0.0200.000

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 head0.014
GPT teacher head0.195
Teacher spread0.181 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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