Recommended C Style and Coding Standards
Bibliographic record
Abstract
This document is an updated version of the Indian Hill C Style and Coding Standards paper, with modifications by the last three authors. It describes a recommended coding standard for C programs. The scope is coding style, not functional organization. 01/14/94 Recommended C Style and Coding Standards L.W. Cannon R.A. Elliott L.W. Kirchhoff J.H. Miller J.M. Milner R.W. Mitze E.P. Schan N.O. Whittington Bell Labs Henry Spencer Zoology Computer Systems University of Toronto David Keppel EECS, UC Berkeley CS&E, University of Washington Mark Brader SoftQuad Incorporated Toronto 1. Introduction This document is a modified version of a document from a committee formed at AT&T's Indian Hill labs to establish a common set of coding standards and recommendations for the Indian Hill community. The scope of this work is C coding style. Good style should encourage consistent layout, improve portability, and reduce errors. This work does not cover functional organization, or general issu...
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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 | 0.018 | 0.214 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.393 | 0.451 |
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".