MétaCan
Menu
Back to cohort
Record W4288040961 · doi:10.2196/41046

Brilliant Ideas Can Come in All Sizes: Research Letters

2022· editorial· en· W4288040961 on OpenAlexaff
Rita Kukafka, Tiffany I. Leung, Günther Eysenbach

Bibliographic record

VenueJournal of Medical Internet Research · 2022
Typeeditorial
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsUniversity of VictoriaJMIR Publications
Fundersnot available
KeywordsThe InternetOriginal researchMedical researchComputer scienceData scienceInternet researchWorld Wide WebPsychologyLibrary scienceMedicine

Abstract

fetched live from OpenAlex

The Journal of Medical Internet Research is pleased to offer "Research Letter" as a new article type. Research Letters are similar to original and short paper types in that they report the original results of studies in a peer-reviewed, structured scientific communication. The Research Letter article type is optimal for presenting new, early, or sometimes preliminary research findings, including interesting observations from ongoing research with significant implications that justify concise and rapid communication.

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)0.091
metaresearch head score (Gemma)0.084
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.173
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0910.084
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.002
Scholarly communication0.0010.000
Open science0.0040.001
Research integrity0.0010.013
Insufficient payload (model declined to judge)0.0110.000

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 head0.116
GPT teacher head0.532
Teacher spread0.415 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Medical Internet ResearchSame topicWikis in Education and CollaborationFrench-language works237,207