Bibliographic record
Abstract
museums.ch ist die Schweizer Museumszeitschrift.Sie wird vom Verband der Museen der Schweiz (VMS) und von ICOM Schweiz -Internationaler Museumsrat herausgegeben.Sie offeriert allen Kulturfachleuten ein Forum zur Diskussion von Belangen rund um die Museen.Gleichzeitig greift sie aktuelle museologische Themen auf und bietet Grundsatzartikel sowie regelmässige Informationen.museums.cherscheint einmal jährlich.museums.chest la revue suisse des musées.Elle est éditée par l'Association des musées suisses (AMS) et ICOM Suisse -Conseil international des musées.Elle offre à l'ensemble des acteurs culturels une plate-forme pour débattre des enjeux muséaux.Elle aborde les thématiques actuelles de la muséographie et propose des articles de fond ainsi que des actualités sur la vie des musées.La revue museums.chparaît une fois l'an.museums.chè la rivista svizzera dei musei.Edita dall'Associazione dei musei svizzeri (AMS) e da ICOM Svizzera -Consiglio internazionale dei musei, essa si pone come piattaforma di discussione per gli addetti ai lavori e offre approfondimenti sul mondo dei musei.In aggiunta ai temi museali d'attualità, la rivista propone articoli di fondo e informazioni regolari.museums.chesce una volta all'anno.museums.ch is the Swiss museums journal edited by the Swiss Museums Association and ICOM Switzerland -International Council of Museums.It provides a forum of discussion on museum issues for experts engaged in all fields of culture.At the same time it addresses current museological topics and features key articles as well as regular information.The journal museums.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.143 | 0.077 |
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".