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Record W2810244557 · doi:10.1002/pmic.201700460

Proteomic Profile of <i>Daphnia pulex</i> using Data‐Independent Acquisition Mass Spectrometry and Ion Mobility Separation

2018· article· en· W2810244557 on OpenAlexafffund
Aaron Steevensz, Robert Gombar, Roland Vergilino, Melania E. Cristescu, Panayiotis O. Vacratsis

Bibliographic record

VenuePROTEOMICS · 2018
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsMcGill UniversityUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDaphnia pulexProteomePulexBiologyProteomicsMass spectrometryGammarus pulexLabel-free quantificationComputational biologyChromatographyChemistryBiochemistryQuantitative proteomicsDaphniaEcologyGene

Abstract

fetched live from OpenAlex

Daphnia pulex is a keystone species for aquatic habitats and an ecological/evolution model organism. Although significant progress has been made on characterizing its genome, the D. pulex proteome remains largely uncharacterized partially due to abnormally high protein degradation during homogenization and emphasis on genomic analysis. In this study, various sample preparation and mass spectrometry acquisition methods are performed for the purpose of improving D. pulex proteome exploration. Benefits for employing both in-gel and in-solution methods of trypsin digestion are observed. Furthermore, acquisition methods employing ion mobility separation greatly increase peptide identification and more than doubled the proteome coverage. Bioinformatic analysis suggests that mitochondrial and hydrolytic activities are enriched in D. pulex compared to closely related invertebrates or Homo sapiens. Also, novel D. pulex proteins possessing putative genome modifying functional domains are identified. Data are available via ProteomeXchange with identifier PXD008455.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score1.000

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)0.0010.000

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 head0.027
GPT teacher head0.309
Teacher spread0.282 · 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 designBench or experimental
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

Citations7
Published2018
Admission routes2
Has abstractyes

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