Bibliographic record
Abstract
Mendel's name more than of any other draws our attention to the personal side in terms of success and failure in science. Mendel lived 19 years after presenting his research findings and died without receiving any recognition for his work. Are premature discoveries things of the past, you may ask? I review the material basis of science in terms of science boundary and field accessibility and analyze the possibility of premature discoveries in different fields of science such as, for example, physics and biology. I conclude that science has reached a stage where progress is being made mostly by pushing the boundary of the known from inside than by leaping across boundaries. As more researchers become engaged in science, and as more publications become open access, on-line, and interactive, the probability of an important discovery remaining buried and going unrecognized would become exceedingly small. Of course, as examples from physics show, a new theory or an important idea can always lie low, unrecognized until it becomes re-discovered and popularized by other researchers. Thus, premature discoveries will become less likely but not forbidden.
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 | 0.062 | 0.238 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.044 |
| Scholarly communication | 0.015 | 0.040 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".