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Record W4237483916 · doi:10.5860/crln.79.11.635

ACRL Annual Report 2017-2018

2018· article· en· W4237483916 on OpenAlexaboutno aff

Bibliographic record

VenueCollege & Research Libraries News · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
FundersAuburn University at MontgomeryMarquette UniversityUniversity of LouisvilleJohns Hopkins UniversityUniversity of WashingtonBrigham Young UniversityGirton College, University of CambridgeNorth Dakota State UniversityYale UniversityAuburn UniversityMcKnight Foundation
KeywordsExcellenceQuarter (Canadian coin)Fiscal yearPolitical scienceValue (mathematics)Plan (archaeology)Library sciencePublic relationsManagementComputer scienceEconomicsGeography

Abstract

fetched live from OpenAlex

This report highlights ACRL’s many accomplishments during the 2018 fiscal year across the four strategic goal areas highlighted in the Plan for Excellence—the value of academic libraries, student learning, research and scholarly environment, and new roles and changing landscapes—along with the association’s enabling programs and services.See the ACRL FY18 4th Quarter Budget Report supplement for additional information.

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)0.005
metaresearch head score (Gemma)0.014
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 score0.315
Threshold uncertainty score0.977

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0020.000
Scholarly communication0.0070.004
Open science0.0030.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.3150.373

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 head0.107
GPT teacher head0.415
Teacher spread0.308 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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