Bibliographic record
Abstract
Abstract The term “sign” is used in semiotics and hermeneutics as an umbrella (portmanteau) word covering all forms of gestures, ciphers, tokens, marks, indices, and symbols that convey human meaning. There have been many philosophical views expressed in the study of human meaning construction. Some thinkers trace the beginning of human cognition by the earliest Homo sapiens to the use of signs. The earliest religious thinkers emphasized some supernatural indicators of the true nature of reality: they understood “signs” in nature as messages. This led to necromancy and other forms of divination. The Chinese Yi Ching (I Ching) was initially based on the reading of tortoise shells. Victory in battle was often seen as a sign of the whim of the gods or of God's pleasure in ancient times. That which was not understood directly had to be fathomed on the basis of conjecture. Greek physicians utilized somatic signs to diagnose disease. They called this process semeiosis.
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.226 | 0.116 |
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".