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Record W2051938890 · doi:10.1157/13112245

Misconduct by researchers and authors

2007· review· en· W2051938890 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

VenueGaceta Sanitaria · 2007
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsScientific misconductConfidentialityMisconductPolitical scienceHumanitiesLibrary scienceLawMedicineArtAlternative medicineComputer science

Abstract

fetched live from OpenAlex

Most scientific research is conducted properly and reported honestly but a few authors invent or manipulate data to reach fraudulent conclusions. Other types of misconduct include deliberately providing incomplete or improperly processed data, failure to follow ethical procedures, failure to obtain informed consent, breach of patient confidentiality, improper award or denial of authorship, failure to declare competing interests, duplicate submission and plagiarism. Editors, peer reviewers and publishers may also act wrongly. Good practice guidelines are available from the International Committee of Medical Journal Editors (The Vancouver Group) and the Council of Science Editors, amongst others. The Committee on Publication Ethics provides flowcharts to assist editors deal with authorial misconduct. Examples are provided of cases involving epidemiological or public health research, reported to COPE over the last 9 years. Suggestions are offered as to how misconduct might be handled in future. Aunque la mayor parte de la investigación científica se realiza y comunica de manera honesta, algunos pocos autores inventan o manipulan los datos para obtener conclusiones fraudulentas. Hay, además, otros tipos de malos comportamientos, como proporcionar deliberadamente información incompleta o mal procesada, vulnerar la confidencialidad de los pacientes, atribuir o denegar improcedentemente la autoría, no declarar algún conflicto de interés, publicar de forma duplicada y el plagio. Los editores y revisores externos también pueden actuar erradamente. El Comité Internacional de Directores de Revistas Médicas (el Grupo de Vancouver) y el Consejo de Editores Científicos han elaborado guías de buena práctica. El Comité de Ética en Publicación proporciona diagramas para ayudar a los editores a afrontar los casos de mal comportamiento. En este trabajo se comentan algunos casos prácticos de mala práctica en investigación en epidemiología y salud pública de entre los abordados por el Comité de Ética de publicación durante los últimos 9 años. Se presentan además sugerencias para tratar estas situaciones en el futuro.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.857
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0050.001

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 head0.877
GPT teacher head0.690
Teacher spread0.187 · 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