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Record W2132930719 · doi:10.1145/2047196.2047218

IP-QAT

2011· article· en· W2132930719 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicExpert finding and Q&A systems
Canadian institutionsAutodesk (Canada)
Fundersnot available
KeywordsComputer scienceContext (archaeology)World Wide WebDatabase transactionSoftwareCloud computingProduct (mathematics)Field (mathematics)Operating systemDatabase

Abstract

fetched live from OpenAlex

We present IP-QAT, a new community-based question and answer system for software users. Unlike most community forums, IP-QAT is integrated into the actual software application, allowing users to easily post questions, answers and tips without having to leave the application. Our in-product implementation is context-aware and shows relevant posts based on a user's recent activity. It is also designed with minimal transaction costs to encourage users to easily post, include annotated images and file attachments, as well as tag their posts with relevant UI components. We describe a robust cloud-based system implementation, which allowed us to release IP-QAT to 37 users for a 2 week field study. Our study showed that IP-QAT increased user contributions, and subjectively, users found our system more useful and easier to use, in comparison to the existing commercial discussion board.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.942
Threshold uncertainty score0.959

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)0.0000.001

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 head0.063
GPT teacher head0.213
Teacher spread0.150 · 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

Quick stats

Citations43
Published2011
Admission routes1
Has abstractyes

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