Bibliographic record
Abstract
This text passes the exposition that the news is regarded as the meaning of the cultural product correctly，Have described from five respects on the issue that how to make benefit of the news products maximize, after analysing to its income mode. Prove news this piece lie cultural industry cultural product importance and his operation mode and method among market , core of layer. Key words: News , news products , cultural product , spread , media , capital market Resume : Ce texte passe l'exposition que les nouvelles sont considerees commela signification du produit culturel correctement, Ont decrit de cinq respects sur la question qui comment faire l'avantage du maximize£¬after de produits de nouvelles analysant a son mode de revenu. Prouvez les nouvelles cette importance culturelle de produit d'industrie culturelle de mensonge de morceau et son mode et methode d'operation parmi le marche, noyau d'une couche. Mots-cles : Nouvelles, produits de nouvelles, produit culturel, ecartez, medias, marche financier 摘要：本文通過對新聞作為文化產品涵義的闡述，在對其收益模式進行分析後，就如何使新聞產品效益昀大化問題從五個方面進行了論述，說明了新聞這個位於文化產業核心層的文化產品在市場中的重要性及其運作模式和方法。 關鍵詞：新聞；新聞產品；文化產品；傳播；媒體；資本市場
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 | 0.001 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.056 | 0.018 |
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".