Nature, Information & [Digital] Technology [NIT]: Introduction & Elements
Bibliographic record
Abstract
Modern era is being characterized by the influence of digital and computer systems. These systems dominate the development of sciences, thus leading to a fuzzy distinction between pure scientific innovation and digital-based progress (e.g. DNA sequencing). However, there is a corresponding directional arrow having as an ending point the face of the digital era; the starting point is ever the origin of natural elements. The contents of this presentation are an attempt to trace in depth and then to provide an overview, as a result of a composite process, of the following assemblage of fundamental elements. These elements refer to the multi-faceted thematic realm of: (a) the ‘physical world’ (the Universe), (b) the information which is usually emitted by this world (though often tacitly), and finally (c) the means and methodology used by modern society in order to deal with this information. The processing of this information is performed, in the vast majority of cases, by means and in terms of digital logic and digital systems. The matter of this presentation should be considered as a generalized introduction to the complete solid of ‘Nature, Information and Technology’ (the NIT whole).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.012 |
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".