Bibliographic record
Abstract
When Embraer's functional Bandeirante turboprop took to the air in 1972, few would have guessed that four decades later the modest government-launched venture would have morphed into one of the world's big four airframers, with a portfolio spanning commercial, business and military aircraft. Embraer's success story is well known, and without it there would be no Brazilian aerospace industry. The now privately owned company still dominates, but a sizeable aerospace industry community has flourished around it, including a network of foreign-owned suppliers and locally owned small and medium-size enterprises. Long-established Eurocopter subsidiary Helibras is entering a new phase of growth, wile the thriving airline sector in Brazil and the rest of South America has provided a lucrative market for service provider such as training specialist CAE, engine maker Rolls-Royce and TAP Maintenance & Engineering in MRO. In this country special, we examine the make-up of Brazil's aerospace sector and its prospects. Decade of departure : with a mature E-Jets business and growing executive jet line-up, overseas expansion and defence will be airframer's next priorities -- Embraer opens up a new front in defence -- Brazil's other OEM : a contract to assemble EC725s for the military has elevated its status. Next step could be an all-Brazilian helicopter -- Made in Brazil : despite Embraer's success, the country has struggled to create a sizeable home-grown supply base. Could this change? -- CAE's pilot strategy : Latin America's thriving airlines are pushing up demand for flightcrew training. The Canadian provider is leading the way -- Taking the high road : Brazil's seer size, increasing wealth and congestion in the cities makes it a lucrative market for VIP jets and helicopters -- TAP turns it on in Brazil : the maintenance division of Portugal's flag carrier saw an opportunity when the MRO arm of Varig came on the market -- Rolls-Royce's 53 years of local heritage.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.065 | 0.010 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".