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Record W7029149757

ILD Software Working Group Meeting

2010· other· en· W7029149757 on OpenAlexaboutno aff

Bibliographic record

VenueInternational Linear Collider · 2010
Typeother
Languageen
FieldArts and Humanities
TopicLinguistics and language evolution
Canadian institutionsnot available
Fundersnot available
KeywordsJoin (topology)PhoneSoftwarePhone callToll
DOInot available

Abstract

fetched live from OpenAlex

Topic: ILD Software WG Phone Meeting \nDate: Wednesday, June 23, 2010 \nTime: 2:00 pm, Europe Summer Time (Berlin, GMT+02:00) \nMeeting Number: 755 738 005 \nMeeting Password: ildsoft \n\n\n------------------------------------------------------- \nTo join the online meeting (Now from iPhones and other Smartphones too!) \n------------------------------------------------------- \n1. Go to https://ilc.webex.com/ilc/j.php?ED=124002602&UID=0&PW=NZTM2ODI3YjZk&RT=MiMyNQ%3D%3D \n2. Enter your name and email address. \n3. Enter the meeting password: ildsoft \n4. Click "Join Now". \n\nTo view in other time zones or languages, please click the link: \nhttps://ilc.webex.com/ilc/j.php?ED=124002602&UID=0&PW=NZTM2ODI3YjZk&ORT=MiMyNQ%3D%3D \n\n------------------------------------------------------- \nTo join the audio conference only \n------------------------------------------------------- \nTo receive a call back, provide your phone number when you join the meeting, or call the number below and enter the access code. \nCall-in toll-free number (US/Canada): 1-866-699-3239 \nCall-in toll number (US/Canada): 1-408-792-6300 \nGlobal call-in numbers: https://ilc.webex.com/ilc/globalcallin.php?serviceType=MC&ED=124002602&tollFree=1 \nToll-free dialing restrictions: http://www.webex.com/pdf/tollfree_restrictions.pdf \n\nAccess code:755 738 005 \n

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)0.007
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.538
Threshold uncertainty score0.660

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.004
Science and technology studies0.0030.001
Scholarly communication0.0110.011
Open science0.0050.008
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.5380.763

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 head0.020
GPT teacher head0.243
Teacher spread0.223 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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