MétaCan
Menu
Back to cohort
Record W2094472262 · doi:10.4018/jmhci.2009062601

How It Started

2009· article· en· W2094472262 on OpenAlexaboutno aff
Evan Koblentz

Bibliographic record

VenueInternational Journal of Mobile Human Computer Interaction · 2009
Typearticle
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsnot available
Fundersnot available
KeywordsThrivingThe InternetComputer scienceMobile deviceQuarter (Canadian coin)Great recessionInternet accessTelecommunicationsInternet privacyWorld Wide WebGeographyEconomicsPsychologyKeynesian economics

Abstract

fetched live from OpenAlex

Internet access on cellular phones, after emerging as a new technology in the mid-1990s, is now a thriving activity despite the global economic recession. IDC reported smartphone sales of 1.18 billion units in 2008 (IDC, 2009), compared to the unconnected personal digital assistants approaching merely 1 million units per quarter in the second half of 2003.However, the concept of using handheld devices for wide area data applications began 25 years prior to the beginning of the end of PDAs

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.075
Threshold uncertainty score0.252

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.006
Scholarly communication0.0150.013
Open science0.0010.006
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0750.026

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 head0.035
GPT teacher head0.320
Teacher spread0.285 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Mobile Human Computer InteractionSame topicContext-Aware Activity Recognition SystemsFrench-language works237,207