We shared this request example with FAB participants: url_qparams = { "limit": count, "offset": offset, "has_group": "false", "order_by": "-activity", "forecast_type": "binary", "project": tournament_id, "status": "open", "type": "forecast", "include_description": "true", } url = f"{api_info.base_url}/questions/" response = requests.get( url, headers={"Authorization": f"Token {api_info.token}"}, params=url_qparams )

But we don't want to support all these parameters, and the ones relevant are: - order_by - status - project - forecast_type - we ignore this, but assume it's binary - FAB only supports binary for now.

GET /api2/questions/?format=api&offset=5480
HTTP 200 OK
Allow: GET, OPTIONS
Content-Type: application/json
Vary: Accept

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            "title": "Will it turn out that Bloomberg manipulated 2020 election prediction markets?",
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                "id": 3671,
                "title": "Will it turn out that Bloomberg manipulated 2020 election prediction markets?",
                "created_at": "2020-02-15T17:10:53.095991Z",
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                "resolution_criteria": "While having a lot of great qualities, prediction markets do have some drawbacks.  For one, betting markets can be manipulated by anyone with enough resources if they do not mind losing some of them (in expectation).  As a case in point, there is some evidence that in 2012 Romney's chances were artificially boosted, and some\n(rank) speculation (see e.g. [here](https://www.vox.com/future-perfect/2020/2/14/21137882/prediction-markets-bloomberg-sanders-president)) that Bloomberg's could be similarly benefitting.  \n\nThe proposition in question will be taken as: \n\n> A major prediction market such as PredictIt, Betfair, or one of comparable liquidity has had 2020 Presidential election results materially changed using bets made with funds tied directly to Bloomberg or his campaign.\n\nThat's not terribly precise, by design. It does not address the source of knowledge or fix many of the details. But this question is a bit experimental, one of a series of \"self-resolving\" ones. Resolution to this question will be determined as follows:\n\n* If at any time after the date of ***2020-12-01*** the community prediction is > 95% or < 5%, the question resolves positively or negatively, respectively.\n\n* Otherwise, on or about the close and resolve date of 2022-01-01, the question will be decided by unanimous vote of a council of three people as to whether the proposition listed above is true, resolving ambiguous in the case of disagreement. The council of three will be chosen by quantum mechanical random numbers from a list of 12 people that will be composed by the author around the time of question close, and held secretly until the time of question resolution.",
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            "title": "Will the PredictIt prediction market outperform Fivethirtyeight's forecasts for the 2020 Super Tuesday Democratic primaries?",
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                "id": 3666,
                "title": "Will the PredictIt prediction market outperform Fivethirtyeight's forecasts for the 2020 Super Tuesday Democratic primaries?",
                "created_at": "2020-02-13T22:27:45.442853Z",
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                "resolution_criteria": "[Nate Silver and his fivethirtyeight site](http://www.fivethirtyeight.com) has achieved significant notoriety for developing a system to carefully aggregate election polls to create well-calibrated statistical forecasts of outcome elections; his site publishes daily updates to predictions for primary and general elections in House, Senate and Presidential races.\n\nPrediction markets have offered an alternative to poll aggregation in forecasting elections.  Markets such as (the now defunct) InTrade, the [Iowa Electronic Markets](http://tippie.uiowa.edu/iem/), [PredictIt](https://www.predictit.org/), and others ask users to buy and sell shares assigned to each candidate in each race, so that the price point corresponds to the probability of victory.  In this question we focus on PredictIt, which allows users to place relatively small real-money bets on candidates.\n\nBoth [fivethirtyeight.com](https://projects.fivethirtyeight.com/2020-primary-forecast/california/) and [PredictIt](https://www.predictit.org/markets/1/Dem-Nomination) have published probabilities for each of the 14 Super Tuesday Primaries on the Democratic side. (The races are California, Texas, North Carolina, Virginia, Massachusetts, Minnesota, Colorado, Tennessee, Alabama, Oklahoma, Arkansas, Utah, Maine, Vermont.)\n\n*Which forecasts will prove to be more accurate?*\n\nTo compare, we will score each set of predictions using a [Brier score](https://en.wikipedia.org/wiki/Brier_score) averaged over all \\(N=14\\) races, computed as\n\\[S = {1\\over N}\\sum_{i=1,N} \\sum_{j=1,M_i} (p_{ij}-o_{ij})^2,\\]\nwhere *j* enumerates the \\(M_i\\) possible outcomes (i.e. possible winners) in the *i*th race out of *N*, where \\(p_{ij}\\) is the forecast probability of candidate *j* winning the *i*th race, and \\(o_{ij}\\) is assigned 1 if candidate *j* wins the *i*th race, and 0 otherwise.\n\nFor example, if PredictIt assigned 52% to Sanders and 48% to Warren in the New York Democratic Primary and if Sanders won then PredictIt would achieve a Brier Score of \n\\[S=(0.52-1)^2+(0.48-0)^2 = 0.4608.\\]\nA lower Brier score is better, with perfect predictions corresponding to \\(S=0\\). (In the case where PredictIt's prices do not add up to $1, we will normalize them to $1 to convert to probabilities.)\n\nThis question resolves positively if the Brier score for the 14 races is lower for PredictIt's probabilities than for fivethirtyeight.com's probabilities, where we will take values as of noon EST on 3/2/2020, and election outcomes as reported on 3/3-3/4.",
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                "resolution_criteria": "[Covid-19](https://en.wikipedia.org/wiki/2019_novel_coronavirus_(2019-nCoV)), also known as Wuhan coronavirus or Wuhan seafood market pneumonia virus, is a positive-sense, single-stranded RNA coronavirus first reported in 2019 and genomically sequenced after nucleic acid testing on a positive patient sample in a patient with pneumonia during [the 2019-2020 Wuhan pneumonia outbreak](https://en.wikipedia.org/wiki/2019%E2%80%9320_outbreak_of_novel_coronavirus_(2019-nCoV)). The virus is [at least 70% similar in genetic sequence to SARS-CoV](https://www.ijidonline.com/article/S1201-9712(20)30011-4/pdf), the [virus that causes severe acute respiratory syndrome](https://en.wikipedia.org/wiki/Severe_acute_respiratory_syndrome-related_coronavirus).\n\nVarious research groups [have started work](https://en.wikipedia.org/wiki/2019_novel_coronavirus#Vaccine_research) on a vaccine to fight the virus, with [some](https://web.archive.org/web/20200125203723/https://www.reuters.com/article/us-china-health-vaccines-idUSKBN1ZN2J8) hoping to start human tests as early as May 2020.\n\nQuestion: **Will a vaccine targeted at the Covid-19 be administered to at least 10,000 people in 2020?**\n\nDetails:\n\n + Resolution will be by credible media report or credible official publication this has happened. This excludes media and institutions affiliated or otherwise under the control of the Chinese government.\n\n + A single vaccine has to be administered to 10000 people.\n\n + A vaccine can trigger: \n\n     + Positive resolution if there is consensus that it protects against Covid-19.\n     + Ambiguous resolution if there is no consensus one way or the other.\n\n + Negative resolution occurs only when there is no vaccine triggering either positive or ambiguous resolution.\n\n + The aforementioned \"consensus\" shall be reached among non-china-affiliated medical professionals, as judged by Metaculus, helped by the discussion in comments below.\n\n + This resolves whenever the relevant media reports are published, or on 2021-01-01 (whichever comes first).\n\n + If this resolves positively, it does not close retroactively (sorry for the lost points).\n\n+ A single vaccine has to be administered to 10000 people.",
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