get_sentiment_distribution

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Aggregate AI polarity, centrality and subjectivity across a filter set. 4 models scored the corpus independently — gpt-5-6-luna, mistral-small-2603, deepseek-v4-flash-0731, gemma-4-31b-it — so model:"all" returns each one's distribution plus how often they AGREE. Treat disagreement as a fact about the judgement rather than noise: corpus-wide the panel is unanimous on polarity for only ~36% of articles, so in a set where the models split no single one's number should be quoted alone. All three scales are ordinal French labels; subjectivity is much the weakest and ships a caveat to quote with it. Articles were scored whether or not their full text ships, so these shares are not subject to the OCR coverage limit; compare scored_by_all against total_articles for the residual gap (the ~51 non-francophone articles are unscored by design).