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Record W4252542232 · doi:10.1002/bult.2014.1720400301

Editor's desktop

2014· article· en· W4252542232 on OpenAlexaboutno aff
Irene L. Travis

Bibliographic record

VenueBulletin of the Association for Information Science and Technology · 2014
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsnot available
Fundersnot available
KeywordsClubEnthusiasmDowntownBedroomLeagueSalonMedia studiesLibrary scienceHistoryVisual artsArt historyArtSociologyPsychology

Abstract

fetched live from OpenAlex

Montreal was a hospitable and popular site for the 2013 Annual Meeting, which was attended by nearly 600 people. In the off-season, downtown Montreal seemed generally dominated by the pleasant bustle of business and students from nearby McGill. All seemed quiet at night, but then there was the noble and magnificent traffic jam after the Canadiens' hockey game Monday night, which we could all view as light sculpture from our perch in the Salon Club at the SIG/III International Reception. The reception was a significant highlight of the meeting as 41 different countries were represented this year. I was especially impressed with the energy and enthusiasm of the newly created Asian Chapter and of the European Chapter, which won the 2013 Chapter-of-the-Year Award. In this issue of the Bulletin, we give you a taste of the Annual Meeting with a look at a variety of conference activities. We begin in Inside ASIS&T with a photo montage of people, places, sessions, parties and other events we enjoyed in Montreal. We then segue into full coverage of the winners of this year's prestigious ASIS&T Annual Awards and a report from the James Cretsos Leadership Award winner Chirag Shah on what ASIS&T means to him both personally and professionally. Continuing the Annual Meeting coverage in our feature section, we begin with reports from pre-conference workshops by SIG/USE, SIG/MET and SIG/SI, in which these active SIGs offered intense programs of papers, speakers, posters, panels, discussion groups and award presentations focused on their own specialties. Steve Hardin reports on the talk by Jorge Garcìa, this year's keynote speaker. We have also included Award of Merit recipient Carol Kuhlthau's acceptance speech as well as viewpoints on information science from ASIS&T Research Award recipient Susan Herring. On his President's Page, Harry Bruce updates us on upcoming actions being taken as a result of the Web Presence Task Force and on steps for expanding membership. And finally, our RDAP Report is by Christopher Eaker of the University of Tennessee Libraries, who discusses resources available for educating researchers, especially graduate students, about data management.

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)0.005
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.006
Open science0.0020.001
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 head0.014
GPT teacher head0.278
Teacher spread0.264 · 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.

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

Citations0
Published2014
Admission routes1
Has abstractyes

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