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Geographic scope of the analyses.

2021· other· en· W6904771100 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFigshare · 2021
Typeother
Languageen
FieldComputer Science
TopicComputability, Logic, AI Algorithms
Canadian institutionsnot available
Fundersnot available
KeywordsEcoregionCensusScope (computer science)Sampling (signal processing)State (computer science)Production (economics)

Abstract

fetched live from OpenAlex

<p>The focal region for identifying native seed production locations was delineated as a one US state or Canadian province buffer around the Level II Temperate Prairie Ecoregion within the upper Midwest USA, which is our sampling region. The map shows the final 483 hypothetical restoration sites (filled black circles) that were used in our analyses. Seed production locations and exotic species distributions were obtained for the focal region of the study. US state and county data are publicly available from the US Census Bureau and are not subject to copyright (<a href="https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.2017.html" target="_blank">https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.2017.html</a>). Canadian province data are publicly available through Statistics Canada and also are not subject to copyright (<a href="https://www150.statcan.gc.ca/n1/en/catalogue/92-160-X" target="_blank">https://www150.statcan.gc.ca/n1/en/catalogue/92-160-X</a>).</p>

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.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.235
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.2350.000

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 head0.082
GPT teacher head0.313
Teacher spread0.231 · 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