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Record W2973199801 · doi:10.1055/s-0039-1696121

Bedeutung von nicht-registriertem Alkohol für die Erfassung des pro-Kopf-Konsums

2019· article· de· W2973199801 on OpenAlex
Charlotte Probst, Jakob Manthey, Jürgen Rehm

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSuchttherapie · 2019
Typearticle
Languagede
FieldSocial Sciences
TopicConsumer behavior in food and health
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsGynecologyMedicine

Abstract

fetched live from OpenAlex

Einleitung Alkoholkonsum ist einer der wichtigsten Risikofaktoren in Europa für Morbidität und Mortalität, auf den etwa 10% der gesamten Krankheitslast zurückzuführen ist. Nicht-registrierter Alkohol, d. h. Alkohol, der nicht in offiziellen Statistiken erfasst wird, macht einen bedeutenden Bestandteil des gesamten Alkoholkonsums aus. Daher sollte nicht-registrierter Alkohol auch bei der Quantifizierung der alkohol-attributablen Krankheitslast berücksichtigt werden.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.005

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 head0.060
GPT teacher head0.368
Teacher spread0.308 · 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