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Record W4381956096 · doi:10.1007/978-3-031-36272-9

Artificial Intelligence in Education

2023· book· en· W4381956096 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLecture notes in computer science · 2023
Typebook
Languageen
FieldEngineering
TopicAdvanced Data Processing Techniques
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Information and Communications TechnologyUniversity of California, IrvineCalifornia State University, FullertonUniversidade Federal de AlagoasUniversity of Colorado BoulderU.S. ArmySingapore Management UniversityStockholms UniversitetUniversity of Massachusetts AmherstUniversidade Federal do Rio de JaneiroUniversidade Federal de PernambucoUniversity of TsukubaTechnion-Israel Institute of TechnologyAteneo de Manila UniversityUniversidad de ChileUniversity of PittsburghHacettepe ÜniversitesiIran Telecommunication Research CenterUniversidad Autónoma de MadridUniversity of PennsylvaniaGeorgia Institute of TechnologyInstituto Tecnológico y de Estudios Superiores de MonterreySimon Fraser UniversityLeibniz-GemeinschaftSapienza Università di RomaGottfried Wilhelm Leibniz Universität HannoverSorbonne UniversitéUniversidad Politécnica de MadridUniversidade Federal de UberlândiaTurun YliopistoU.S. Army Combat Capabilities Development CommandAthabasca UniversityUniversity of MinnesotaUniversiteit UtrechtTrinity College DublinUniversidad del CaucaUniversity of SussexUniversidade Federal do Rio Grande do SulUniversity of AlbertaUniversidad Nacional de Educación a DistanciaArizona State UniversityUniversitat Pompeu FabraUniversité de LorraineNorth Carolina State UniversityCarnegie Mellon UniversityUniversité de LyonUniversity of Technology SydneyUniversity of Central FloridaUniversity of Southern CaliforniaUniversity of MemphisUniversità degli Studi di CagliariUniversity of South AustraliaMcGill UniversityBeijing Normal UniversityVanderbilt UniversityEuskal Herriko UnibertsitateaKanazawa UniversityUniversiteit van AmsterdamGeorgia State UniversityUniversity of Illinois at Urbana-ChampaignColorado State UniversityKindai UniversityÉcole Polytechnique Fédérale de LausanneValparaiso UniversityNorthern Illinois UniversityEducational Testing ServiceNorthern Kentucky UniversityUniversity College London
KeywordsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.850
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.295
Teacher spread0.274 · 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