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Record W7072102291

UMaine/ University of New Brunswick Graduate History Conference

2012· article· en· W7072102291 on OpenAlexaboutno aff

Bibliographic record

VenueDigitalCommons (California Polytechnic State University) · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipTheme (computing)Graduate studentsEvent (particle physics)Higher education
DOInot available

Abstract

fetched live from OpenAlex

For the past fourteen years the University of Maine and University of New Brunswick have hosted a collaborative graduate student conference to showcase the scholarship of emerging graduate students in the fields of history and Canadian-American studies. The conference is hosted biannually by the University of Maine History Department, and organized by the History Graduate Student Association (HGSA). The next conference will be at the University of Mainet. on October 12th-14th,2012. Out conference theme for this year is "On the Margins," and will include such areas as gender history, public history, and North American borderlands history. We have formed an organizing committee to fund-raise and coordinate this important Canadian-American event. Dr. Gail Campbell, Professor of History at the University of New Brunswick, has graciously agreed to deliver our keynote address on October 12. Our conference will be a showcase event for the Canadian-American Center, the History Department, and the University of Maine. This student-run event will attract a wide range of graduate students and faculty from around the university, as well as researchers and scholars from around the United States and Canada.In addition, we have arranged a private Directors Tour" of the Page Farm and Home Museum on campus for the Saturday afternoon of the conference to highlight this excellent resource. As part of our strategy to attract more participants, we have voted to institute a prize for best conference paper.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.647
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.201
Teacher spread0.161 · 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
Published2012
Admission routes1
Has abstractyes

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