Bibliographic record
Abstract
Although linguistics may treat languages as a syntactic and/or semantic entity that regulates both language production and comprehension, this article perceives that language is a physical and a biological phenomenon. The biological view of languages presents a new metaphor on an evolutionary time-scale the human brain and human language have co-evolved. Therefore, the brain is the instrument with a repository of syntactic and semantic constraints. The logical vocabulary of natural languages has been understood by many as a purified abstraction in formal sciences, where the internal transactions of reasonings are constrained by the logical laws of thought. Although no vocabulary can be entirely independent of semantic understanding, logical vocabulary has fixed minimal semantic content independent of context. Therefore, logic is centered in linguistic evolution by observing that all connective vocabulary descends from lexical vocabulary based on spatial relationship of sentences. Far from having fixed minimal semantic content, logical vocabulary is semantically rich and context-dependent. Many cases of mutations in logical vocabulary and their semantic changes have been observed as similar to that of biological mutations. These changes proliferate to yield a wide diversity in the evolved uses of natural language connectives.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".