Bibliographic record
Abstract
Our mother Kirsti and our father Kari 2 had four sons: Eerik (b.1956), Juhani (b.1959) 3 and the two of us (b.1963).Our mother was once asked if it was easier to have one, two or more kids.She replied jokingly, that the hardest time was when she had three.Olli and I were born on the morning of 23 February at the Turku University central hospital, with the interval of twenty minutes.That means that I know him not only from our birth on, but even from some months before.Our parents, both born in Helsinki, moved to Turku in 1957, at a time in a phase of rapid growth.In a few years, Father received a professorship in Biology, and Mother in Psychology.Many scholars of the same generation in Helsinki made the same move, and while in Turku, they kept close contacts throughout decades.However, Turku was never a new place for our parents, as they both had deep 4 descending from a family in Westrobothnia in present Sweden, received his theological exam in Turku in 1827, a few weeks before the great fire that destroyed most of the town and resulted in the uni-keepers in Turku and had relations with old families in the region. 5 6 had in 1853 purchased Metsmki, a manor house in the vicinity, and two of his sons (out of eight children) became principals of the Finnish and Swedish Gymnasiums of the city. 7 until 1976.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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; both teacher heads agree on what is shown here.
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".