发生了什么变化

下面每一条都是**已经发生**的变化,并附上触发它的数字。Kanon 做的是检测,不是预言。

120 持续
持续 x1 productivity

61d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 61d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

60d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 60d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

61d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 61d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

61d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 61d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

61d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 61d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

63d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 63d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

59d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 59d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

60d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 60d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

60d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 60d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

60d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 60d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

62d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 62d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

58d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 58d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

59d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 59d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

59d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 59d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

59d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 59d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

61d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 61d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

57d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 57d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

58d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 58d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

58d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 58d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

58d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 58d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

60d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 60d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

56d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 56d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

57d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 57d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

57d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 57d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

57d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 57d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

59d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 59d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

55d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 55d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

56d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 56d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

56d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 56d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

56d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 56d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

58d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 58d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

54d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 54d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

55d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 55d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

55d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 55d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

55d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 55d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

57d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 57d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

53d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 53d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

54d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 54d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

54d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 54d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

54d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 54d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

56d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 56d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

52d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 52d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

53d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 53d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

53d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 53d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

53d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 53d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

55d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 55d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

51d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 51d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

52d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 52d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

52d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 52d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

52d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 52d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

54d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 54d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

50d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 50d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

51d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 51d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

51d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 51d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

51d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 51d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

53d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 53d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

49d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 49d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

50d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 50d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

50d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 50d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

50d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 50d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

52d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 52d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

48d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 48d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

49d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 49d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

49d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 49d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

49d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 49d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

51d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 51d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

47d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 47d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

48d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 48d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

48d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 48d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

48d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 48d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

50d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 50d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

46d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 46d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

47d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 47d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

47d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 47d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

47d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 47d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

49d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 49d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

45d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 45d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

46d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 46d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

46d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 46d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

46d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 46d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

48d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 48d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

44d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 44d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

45d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 45d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

45d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 45d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

45d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 45d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

47d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 47d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

43d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 43d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

44d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 44d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

44d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 44d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

44d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 44d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

46d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 46d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

42d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 42d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

43d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 43d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

43d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 43d 置信度 0.85 signal-v1 证据 时间线
持续 Flare coding

43d after the breakout, producthunt_votes is 120 vs 110 at breakout — still above baseline

breakout@110 → now@120 窗口 43d 置信度 0.85 signal-v1 证据 时间线
持续 Aximote data

45d after the breakout, producthunt_votes is 201 vs 0 at breakout — still above baseline

breakout@0 → now@201 窗口 45d 置信度 0.85 signal-v1 证据 时间线
持续 x1 productivity

41d after the breakout, producthunt_votes is 516 vs 367 at breakout — still above baseline

breakout@367 → now@516 窗口 41d 置信度 0.85 signal-v1 证据 时间线
持续 Ninjō AI sales

42d after the breakout, producthunt_votes is 121 vs 111 at breakout — still above baseline

breakout@111 → now@121 窗口 42d 置信度 0.85 signal-v1 证据 时间线
持续 Purchase API by Agentcard ecommerce

42d after the breakout, producthunt_votes is 126 vs 104 at breakout — still above baseline

breakout@104 → now@126 窗口 42d 置信度 0.85 signal-v1 证据 时间线
检测器 signal-v1。公开阈值:加速 = 本窗增量 ≥ 前窗的 1.5 倍(且至少 +5);降温 = 动量掉到前窗的 40% 以下;重启 = 静止 7 天后重新变动;异常 = 相对它自己的历史 |z| ≥ 3。上面每一个数都可以拿这些常数复算。机器口:/api/v2/changes。