Sex Ratio of Twin at Birth and its Significance in Population Management
Bibliographic record
Abstract
Abstract In clue of twins, this paper studies the sex ratio of twin at birth and its functions in population science, explores to exploit deeply the information of twin birth in China which was hidden in data structure of Censuses and bearing investigations, and raises the possibilities of analyzing the natural sex ratio at birth and evaluating the reliability of sex ratio at birth in China. The goal of this paper is to give a suggestion for exploiting and studying the data of the sixth Census deeply. Key words : Twin; Sex ratio at birth; Census; Population Management Resume Dans les idees de jumeaux, ce document etudie le sex-ratio a la naissance de jumeaux et de ses fonctions dans les sciences de la population, il explore profondement a exploiter les informations de naissance de jumeaux en Chine, qui etait cache dans la structure des donnees des recensements et des enquetes portant, et souleve la possibilite d’analysant le sex-ratio a la naissance naturelle et d'evaluer la fiabilite des sex-ratio a la naissance en Chine. L'objectif de ce texte est de donner une suggestion pour l'exploitation et l'etude des donnees du Recensement de sixieme profondement. Mots cles : Jumeaux; Naissance du Sexe-ratio; Recensement; Gestion de la population
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".