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Record W7056878848

How can new strategies foster the air cargo sector in the Lisbon airport, while dealing with the limited capacity and inadequacy of the air cargo infrastructures?

2018· dissertation· en· W7056878848 on OpenAlexfundno aff

Bibliographic record

VenueRepositório do ISCTE-IUL · 2018
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersIndigenous and Northern Affairs Canada
KeywordsAir cargoProduct (mathematics)AviationKey (lock)Face (sociological concept)
DOInot available

Abstract

fetched live from OpenAlex

Air cargo in Portugal, despite its undeniable importance for the Portuguese economy, is still seen by some agents as a poor relative of passenger transportation, as a by-product, not as a product that, per se has tremendous potential for wealth generation. It is of fundamental importance, that the Lisbon airport and all its stakeholders are aware of this reality, under the risk of losing an important lever of economic growth, and this research is expected to contribute to this intent. Within this setting, this thesis aims to improve the operational performance within the airfreight sector in Lisbon, proposing new strategies to increase efficiency, while dealing with the limited capacity and inadequacy of the current air cargo infrastructures. By initially characterizing the sector, and subsequently identifying the main causes for the problem of limited capacity, a direct comparison can be made with the reality of some key industry European airports. Hence, allowing the finding of solutions for solving the identified causes to the main problem, and thereby uncovering the winning strategies to face possible constraints to a greater vitality of the air cargo sector in Lisbon.

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 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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.231
Teacher spread0.218 · 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 teacher head, 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
Published2018
Admission routes1
Has abstractyes

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