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Record W7004942800

Pacific alliance allies and its commercial opportunities with Colombia

2018· dissertation· en· W7004942800 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

VenueIcesi Digital Library (Icesi University) · 2018
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Diversity and Evolution
Canadian institutionsnot available
Fundersnot available
KeywordsAllianceLatin AmericansDynamismDeveloping countryContext (archaeology)Security councilSouth–South cooperationSustainabilityTrade agreementFree trade
DOInot available

Abstract

fetched live from OpenAlex

According to the Americas Society / Council of the Americas, the members of the P.A. account
\naround 37% of Latin America’s total GDP, 50% of the country’s exports and 45% of foreign
\ninvestment. ( Americas Society / Council of the Americas, 2018). Due to de dynamism of this
\nalliance the world has started to interest in it. Now, the P.A. has about 52 observer countries who
\ncan participate of the meetings of the Alliance and can also apply to become a full member of the
\nP.A. if they have trade deals in place with at least half of the coalition’s full members. They are,
\nin America: Argentina, Canada, Costa Rica, Ecuador, El Salvador, United States, Guatemala,
\nHaiti, Honduras, Panama, Paraguay, Dominican Republic, Trinidad and Tobago, and Uruguay. In
\nAfrica: Egypt and Morocco. In Asia: China, Korea, India, Indonesia, Israel, Japan, Singapore, and
\nThailand. In Europe: Germany, Austria, Belgium, Croatia, Denmark, Slovakia, Slovenia, Spain,
\nFinland, France, Georgia, Greece, Hungary, Italy, Lithuania, Norway, Netherlands, Poland,
\nPortugal, United Kingdom, Czech Republic, Romania, Sweden, Switzerland, Turkey, and Ukraine.
\nAnd last in Oceania: Australia and New Zeeland. Now, there are already two countries in the
\nprocess to access as full member to the P.A., Costa Rica and Panama. (International Centre for
\nTrade and Sustainable Development, 2018)

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.702

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 studies0.0010.000
Scholarly communication0.0000.004
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.156
Teacher spread0.132 · 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