Ref: ISO_IEC_FDIS_14496-17__E_.pdf: Coding of audio-visual objects-- Part 17: Streaming text format (Attached)
Bibliographic record
Abstract
Comment accompanying the Canadian ballot on the above document after a discussion initiated by Uma in the Canadian committee for CAC JTC1: 'The Canadian National Body feels that section 7.4.2 does not clearly specify whether a Byte Order Mark is required in UTF text. This is an issue when a receiver decodes a UTF-16 bit stream. Without the Byte Order Mark, there is no way to determine whether the text has been encoded as UTF-16 BE or UTF-16 LE. Although it may be implicit that the marker must be present. The Canadian National Body suggests adding the following text in section 7.4.2. "The Byte Order Marker shall be present in all UTF encoded text " will make the standard much clearer.' The Canadian National Body notes that when a receiver is only required to decode UTF-16 BE text, but UTF-16 LE text is allowed to be placed in the bitstream, that important text could be omitted during the decoding process. We feel that this means that to allow for interoperability, the encoder in a practical sense will only be able to encode in Big Endian. The Canadian National Body asks to have UTF-16 LE decoding be removed as optional and added as a requirement.. The Canadian National Body notes the following editorial issue. Section 7.4.2 The last sentence in the first paragraph should read: "3GPP text stream receivers shall be able to decode UTF-16 encoded text strings in big endian order. Response received from the editor Jan vanderMeer
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.223 | 0.256 |
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".