Corrigendum: Early attachment and the development of social communication: A neuropsychological approach
Bibliographic record
Abstract
Corrigendum on: Jethava, V., Kadish, J., Kakonge, L., & Wiseman-Hakes, C. (2022). Early Attachment and the Development of Social Communication: A Neuropsychological Approach. Frontiers in Psychiatry, 613.In the original article, the following references were incorrectly cited and should be deleted:• 34. Duffy SN, Craddock KJ, Abel T, Nguyen PV. Environmental enrichment modifies the PKA-dependence of hippocampal LTP and improves hippocampus-dependent memory. Learn Mem. (2001) 8:26-34. doi: 10.1101 The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.A) In the original article, the following articles were not cited:• Hanno E, Surrain S. The direct and indirect relations between self-regulation and language development among monolinguals and dual language learners. Clinical Child and Family Psychology Review. ( 2019 The authors apologize for these errors and state that this does not change the scientific conclusions of the article in any way. The original article has been updated. (1995)
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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 | 0.003 | 0.030 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.064 | 0.048 |
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".