Bibliographic record
Abstract
Abstract Babbling is made up of meaningless speechlike syllables called canonical syllables. Canonical syllables are characterized by the coordination of consonantal and vocalic elements in syllables that have speechlike timing, phonation, and resonance characteristics. Infants begin to babble on average at approximately seven months of age. Babbling continues in parallel with less mature noncanonical vocalizations that make up the majority of utterances through the first year. Babbling also continues in parallel with the emergence of meaningful speech during the second year. Regardless of the language that the infant is learning, most canonical syllables have a CV shape with the consonant being a labial or alveolar stop or nasal and the vowel most likely to be central or low- to mid-front in place (e.g., [bʌ], [da], [mæ]). Approximately 15% of canonical utterances consist of multisyllable strings; in other words, most babbled utterances contain only a single CV syllable. The onset of the canonical babbling stage is crucially dependent upon normal hearing, permitting access to language input and feedback of self-produced speech. Many studies have reported differences in the phonetic and acoustic characteristics of babble produced by infants learning different languages. These differences include the frequency with which certain consonants are produced, the location, size, and shape of the vowel space, and the rhythmic and intonation qualities of multisyllable babbles, in each case reflecting specificities of the input language. However, replications of these findings are rare and further research is required to better understand the learning mechanisms that underlie language specific acquisition of articulatory representations during the prelinguistic stage of vocal development.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".