Bibliographic record
Abstract
Ich habe mit Familie Courtel einen wirklich exzellenten Abend verbracht. Die Töchter sind entzückend, sehr lebhaft und froh, ihren Vater während ihrer Schulferien zur Tagung begleiten zu können. Wir haben auf der zauberhaften Terrasse eines Restaurants in Saint-Sulpice gegessen, ein paar Kilometer von Lausanne entfernt. Danach sind wir gegen 23 Uhr ins Hotel zurückgekehrt. Inspektor Bonvin aus Genf saß gerade in der Lobby, um ihn herum einige Personen, die, so scheint mir, nicht an der COPS-Tagung teilnehmen. Er wirkte sehr besorgt, sicherlich wegen einer laufenden Ermittlung, die ihm offenbar schwer zu schaffen macht. Er begrüßte mich und sagte, dass er vielleicht am Folgetag meine Dienste in Anspruch nehmen müsste. Er wünschte mir eine gute und erholsame Nacht und setzte seine lebhafte Diskussion mit seinen Leuten fort.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.083 | 0.041 |
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".