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Record W6887501564 · doi:10.1594/pangaea.981859

Climate Parameters for the Tajik-Uzbek Surface Data Base

2025· dataset· en· W6887501564 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

VenuePublishing Network for Geoscientific and Environmental Data (PANGAEA) (Alfred Wegener Institute for Polar and Marine Research) · 2025
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicEngineering and Agricultural Innovations
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsPrecipitationMean radiant temperatureSampling (signal processing)Quarter (Canadian coin)AridSurface air temperatureAir temperatureAridity index

Abstract

fetched live from OpenAlex

This dataset contains the climate parameters for each sampling site of the Tajik-Uzbek Surface Data Base (TUSDB). The parameters have been extracted from WorldClim2 (Fick and Hijmans, 2017), except the Aridity Index (AI) which comes from the CGIAR database (Trabucco and Zomer, 2018). The other climate parameters are Mean Annual Air Temperature (MAAT); Mean Annual Precipitation (MAP); Mean Precipitation of Coldest Quarter (MPCOQ); Mean Precipitation of Warm Quarter (MPWAQ); Mean Temperature of the Coldest Quarter (MTCOQ); Mean Temperature of the Warmest Quarter (MTWAQ).

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.024
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0030.004
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 head0.101
GPT teacher head0.288
Teacher spread0.187 · 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