You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 menu
【Schema】
# Table: Menu
[
(id:INTEGER, Primary Key, Examples: [12463, 12464, 12465]),
(name:TEXT, Examples: [The Modern, Restaurant, El Fuerte Del Palmar]),
(sponsor:TEXT, Examples: [HOTEL EASTMAN]),
(event:TEXT, Examples: [BREAKFAST, [DINNER], FRUHSTUCK/BREAKFAST;]),
(venue:TEXT, Examples: [COMMERCIAL, SOC;, EDUC;]),
(place:TEXT, Examples: [HOT SPRINGS, AR]),
(physical_description:TEXT, Examples: [CARD; 4.75X7.5;]),
(occasion:TEXT, Examples: [EASTER;, ANNIVERSARY;, DAILY;]),
(notes:TEXT),
(call_number:TEXT, Examples: [1900-2822, 1900-2825, 1900-2827]),
(keywords:TEXT),
(language:TEXT),
(date:DATE, Examples: [1900-04-15]),
(location:TEXT, Examples: [Hotel Eastman]),
(location_type:TEXT),
(currency:TEXT, Examples: [Dollars, Cents, Francs]),
(currency_symbol:TEXT, Examples: [$, c, FF]),
(status:TEXT, Examples: [complete]),
(page_count:INTEGER, Examples: [2, 4, 12]),
(dish_count:INTEGER, Examples: [67, 34, 84])
]
# Table: MenuItem
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(menu_page_id:INTEGER, Examples: [1389, 3079, 1388]),
(price:REAL, Examples: [0.4, 0.6, 0.5]),
(high_price:REAL, Examples: [1.0, 3.0, 1.5]),
(dish_id:INTEGER, Examples: [1, 2, 3]),
(created_at:TEXT, Examples: [2011-03-28 15:00:44 UTC]),
(updated_at:TEXT, Examples: [2011-04-19 04:33:15 UTC]),
(xpos:REAL, Examples: [0.111429, 0.438571, 0.14]),
(ypos:REAL, Examples: [0.254735, 0.261922, 0.26272])
]
# Table: Dish
[
(id:INTEGER, Primary Key, Examples: [1, 2, 3]),
(name:TEXT, Examples: [Consomme printaniere royal]),
(description:TEXT),
(menus_appeared:INTEGER, Examples: [8, 111, 14]),
(times_appeared:INTEGER, Examples: [8, 117, 14]),
(first_appeared:INTEGER, Examples: [1897, 1895, 1893]),
(last_appeared:INTEGER, Examples: [1927, 1960, 1917]),
(lowest_price:REAL, Examples: [0.2, 0.1, 0.25]),
(highest_price:REAL, Examples: [0.4, 0.8, 1.0])
]
# Table: MenuPage
[
(id:INTEGER, Primary Key, Examples: [119, 120, 121]),
(menu_id:INTEGER, Examples: [12460, 12461, 12462]),
(page_number:INTEGER, Examples: [1, 2, 3]),
(image_id:REAL, Examples: [1603595.0, 1603596.0, 1603597.0]),
(full_height:INTEGER, Examples: [7230, 5428, 3074]),
(full_width:INTEGER, Examples: [5428, 7230, 2046]),
(uuid:TEXT, Examples: [510d47e4-2955-a3d9-e040-e00a18064a99])
]
【Foreign keys】
MenuItem.dish_id=Dish.id
MenuItem.menu_page_id=MenuPage.id
MenuPage.menu_id=Menu.id

    【Question】
    How many percent of Bluefish dishes are located at the center of the menu page? percent = MULTIPLY(DIVIDE(SUM(xpos BETWEEN 0.25 AND 0.75 and ypos BETWEEN 0.25 AND 0.75), COUNT(id)), 1.0); Bluefish is a sub name of dish; located at the center of the menu page refers to xpos BETWEEN 0.25 AND 0.75 and ypos BETWEEN 0.25 AND 0.75;

    【Evidence】
    percent = MULTIPLY(DIVIDE(SUM(xpos BETWEEN 0.25 AND 0.75 and ypos BETWEEN 0.25 AND 0.75), COUNT(id)), 1.0); Bluefish is a sub name of dish; located at the center of the menu page refers to xpos BETWEEN 0.25 AND 0.75 and ypos BETWEEN 0.25 AND 0.75;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT CAST(SUM(CASE WHEN T2.xpos BETWEEN 0.25 AND 0.75 AND T2.ypos BETWEEN 0.25 AND 0.75 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.id) FROM Dish AS T1 INNER JOIN MenuItem AS T2 ON T1.id = T2.dish_id WHERE T1.name LIKE '%BLuefish%'