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Record W4387913726 · doi:10.12957/cadinf.2023.75934

A Never-Ending Story: Revisiting Requirements Major Misunderstandings

2023· article· pt· W4387913726 on OpenAlexfundno aff
Julio César Sampaio do Prado Leite

Bibliographic record

VenueCadernos do IME - Série Informática · 2023
Typearticle
Languagept
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsnot available
FundersPontifícia Universidade Católica do Rio de JaneiroUniversidade do Estado do Rio de JaneiroUniversità degli Studi di TrentoUniversity of California, IrvineUniversity of TorontoCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorConselho Nacional de Desenvolvimento Científico e TecnológicoTechnische Universität Kaiserslautern
KeywordsRomanceHumanitiesArtPhilosophyLiterature

Abstract

fetched live from OpenAlex

A medalha mágica é central no romance de Michael End. Esta medalha mostra duas cobras mordendo uma à outra, em um enlace. A crença popular diz que o desenho da medalha mudou para o filme de Wolfgang Petersen, ressaltando, na imagem, uma sensação de infinito ainda maior. Essa medalha tornou-se um amuleto para os fãs da estória. Esse artigo irá brotar uma visão ampla no campo de requisitos, comparando-a à busca de Percival pelo cálice sagrado. Utilizando metáforas acadêmicas e da cultura popular o artigo afirma que a engenharia de requisitos é um processo educacional, que deve ser feito com transparência. Equívocos históricos sobre requisitos são revistos, armadilhas a serem evitadas são apontadas e novos caminhos a serem construídos são propostos.

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)0.013
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0080.012
Scholarly communication0.0120.020
Open science0.0020.007
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0080.002

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 head0.065
GPT teacher head0.319
Teacher spread0.253 · 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 designQualitative
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

Citations1
Published2023
Admission routes1
Has abstractyes

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