MétaCan
Menu
Back to cohort
Record W2550508329 · doi:10.1145/2992154.2996873

Exploring Genetic Mutations on Mitochondrial DNA Cancer Data with Interactive Tabletop and Active Tangibles

2016· article· en· W2550508329 on OpenAlexafffund
Roozbeh Manshaei, Nauman Baig, Sean DeLong, Shahin Khayyer, Brien East, Ali Mazalek

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsComputer scienceMitochondrial DNAHuman–computer interactionData scienceDNA sequencingDNABiologyGeneticsGene

Abstract

fetched live from OpenAlex

Biological data is becoming so complex, it is difficult for scientists and other professionals to interpret and understand it. New tools are needed to better support the manipulation and understanding of data in order to improve analyses and the formation of new hypotheses. Tangible mtDNA is an active tangible and tabletop system that allows multiple users with diverse expertise to collaborate in exploring and understanding mitochondrial DNA sequencing data in breast cancer patients. In an evaluation of the system, 5 expert biologists found it to be effective for data exploration and useful in supporting understanding, collaboration and discussion of DNA datasets.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.377
GPT teacher head0.408
Teacher spread0.030 · 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 designOther design
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

Explore more

Same topicScientific Computing and Data ManagementFrench-language works237,207