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Record W4410045708 · doi:10.21983/p3.0014.1.16

Distributed Evidence

2012· book-chapter· en· W4410045708 on OpenAlexaff
Jane Hutton

Bibliographic record

VenuePunctum Books · 2012
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This project maps a series of boulders that were plucked, transported, and deposited by the toe-line of the retreating Late-Wisconsin and pre-Wisconsin ice sheets in North America and subsequently named, relocated, modified, and celebrated by people. They are the glacially distributed sites of council meetings, picnics, political movements, and territorial markers. They are inscribed with discrepant personal, regional, and national narratives and at the same time they declare their foreign origin through their conspicuous mineral composition and form. In the mid-19th century such boulders served as critical evidence for piecing together a theory of glaciation, and consequently an idea of geologic time and the location of humans within it. While their scientific importance waned in the 20th century, outside and along-side geology they are critical objects for reflections on time and space of various scales and consequences. They refer simultaneously to different moments in time: their geogenic forma-tion, their glacial deposition, and specific events in cultural history, as they are sometimes literally carved with a date. They are heavy, insistent markers in space, yet they indicate a remote origin—and therefore the journey between two sites—and they continue to be moved or changed by ensuing human forces. The naming, photographing, and feting of the boulders collated and mapped here signal their role as persistent devices for locating deep time within the present and grappling with the continuum of geological and human action.

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 categoriesMeta-epidemiology (narrow)
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 score0.311
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 communication0.0000.000
Open science0.0000.000
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 head0.279
Teacher spread0.239 · 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
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
Published2012
Admission routes1
Has abstractyes

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