For my idea described above here, to illustrate the points adjustments one would have to write some code that simulates a cohort of activators, each adjusting summits from the DB by certain values using non-uniform random sampling from a distribution centered near some value, and additionally simulates the accrual of adjustments over time. That’s doable. One could plot it then as a time series to see how the values of summits are growing or dropping. The center values would not be real. To make them closer to real one would have to look for actual feedback from activators, or comments about the summits, e.g. look into reflector DB with activation reports, see what people say (“dammit that should have been 50 not 10 points”), or into articles associated with summits. Still doable… but is there appetite for this.
For the second part of my idea (summits which have 0 activations and are presumably difficult), this is even simpler, I just did a rough simulation, hope the AI didn’t make any mistakes in coding because I was too lazy to write the calculation code myself this evening. Here are top 10-point summits which have never been activated, but have a certain number of 10-point summits close to them (within 10 km radius) which have been activated more than 5 times. The number of such summits in proximity is listed too.
Probably very good candidates to significantly increase point value, but of course would have to be manually reviewed. Only currently active summits included.
Piz Bever,13
Piz Bleis Marscha,13
Piz Prüna,11
Kurobebetsusan,10
Piz da las Blais,10
Nakayama,8
Piz Cambrena,8
Piz Duan,8
Chastelhorn,7
Hoch Dukan/Piz Ducan,7
La Tsavre/Mont Ferret,7
Piz Paradis,7
Piz Serengia,7
Piz Uffiern,7
Rocca San Giovanni,7
Roche des Prés,7
Senninyama,7
Corn da Camp,6
(...400+ more...)
Some ad-hoc eyeballing shows that they are indeed damn difficult. The full list of potential “difficult summits with easy neighbors” where the number of neighbors activated > 5 times is at least 2, has over 400 candidates.
One could dive more into this and refine the algorithm, and the code, and start the discussion about by how much to increase value, what to do with the already-activated neighbors which will now be cooperatively undervalued, or how to simulate adjustments by activators (first part of my idea), then one would have to devise a process of manual reviews of adjustments which is an exercise in running a distributed moderation business, all doable, but one needs to see the appetite for this while there seems to be none.