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Record W7043807082

Učinci Sjevernoameričkog sporazuma o slobodnoj trgovini za Kanadu

2021· dissertation· hr· W7043807082 on OpenAlexaboutno aff

Bibliographic record

VenueFPZG (University of Zagreb) · 2021
Typedissertation
Languagehr
FieldComputer Science
TopicWireless Sensor Networks for Data Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsConjunction (astronomy)Work (physics)Context (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

U ovom diplomskom radu proučavaju se učinci Sjevernoameričkog sporazuma o slobodnoj trgovini (Northern American Free Trade Agreement) za Kanadu. Ovaj trgovinski sporazum sklopljen je 1994. godine između SAD-a, Meksika i Kanade u svrhu postizanja konkurentnosti područja slobodne trgovine. Glavni cilj rada je prikazati konačne učinke liberalizacije trgovine na gospodarstvo Kanade u smislu utjecaja na poljoprivredu i investiranje te na kanadsku socijalnu politiku u vidu rada, odnosno zapošljavanja i migracija. Također, u radu su obuhvaćeni i teorijski stavovi o liberalizaciji trgovine kao i konceptu međuovisnosti država. Osim toga, na kraju rada je preispitana perspektiva NAFTA-e kao i ono što donosi nasljednik NAFTA trgovinskog sporazuma USMCA (United States-Mexico-Canada Agreement).\n U svrhu postizanja boljeg uvida u učinke Sjevernoameričkog sporazuma o slobodnoj trgovini za Kanadu, istraživanje je provedeno na temelju iščitavanja relevantne domaće i strane stručne literature, pri čemu su neki podaci u radu prikazani i statističkim metodama.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0040.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0300.002

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 head0.011
GPT teacher head0.202
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes1
Has abstractyes

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