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Record W2462601922 · doi:10.1016/j.dib.2016.06.013

Human lung epithelial cell A549 proteome data after treatment with titanium dioxide and carbon black

2016· article· en· W2462601922 on OpenAlexafffund
Ngoc Q. Vuong, Patrick Goegan, Susantha Mohottalage, Dalibor Breznan, Marianne B. Ariganello, Andrew Williams, Fred Elisma, Subramanian Karthikeyan, Renaud Vincent, Premkumari Kumarathasan

Bibliographic record

VenueData in Brief · 2016
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsHealth CanadaUniversity of Ottawa
FundersHealth CanadaClean Air Regulatory Agenda
KeywordsRefSeqProteomeA549 cellProteomicsMass spectrometryChemistryHuman lungCarbon blackTitanium dioxideCarbon dioxideLungBiochemistryCellChromatographyMedicineInternal medicineMaterials scienceGene

Abstract

fetched live from OpenAlex

Here, we have described the dataset relevant to the A549 cellular proteome changes after exposure to either titanium dioxide or carbon black particles as compared to the non-exposed controls, "Proteomic changes in human lung epithelial cells (A549) in response to carbon black and titanium dioxide exposures" (Vuong et al., 2016) [1]. Detailed methodologies on the separation of cellular proteins by 2D-GE and the subsequent mass spectrometry analyses using MALDI-TOF-TOF-MS are documented. Particle exposure-specific protein expression changes were measured via 2D-GE spot volume analysis. Protein identification was done by querying mass spectrometry data against SwissProt and RefSeq protein databases using Mascot search engine. Two-way ANOVA analysis data provided information on statistically significant A549 protein expression changes associated with particle exposures.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.438

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 science0.0010.001
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 head0.020
GPT teacher head0.280
Teacher spread0.259 · 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 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

Citations4
Published2016
Admission routes2
Has abstractyes

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