The TSScienceCollaboration algorithm (US patent number 10, 043,134 ) combines member contributions logically, point by point. On TSScienceCollaboration, a statement is rated Tentatively Established if and only if an unrefuted proof is provided. If you don't believe the proof is adequate, you may challenge it if you can state a rational reason why you don't believe the proof. A challenged proof is not considered Tentatively Established unless and until someone explains what's wrong with the rebuttal.

Other debate sites present somebody's opinion, they don't combine multiple inputs logically. They decide by voting, which leads to groupthink. Many things that are believed true by a majority can be established as being delusional or propaganda.

TSScienceCollaboration is not for establishing those. If you want to add a topic or a statement to TSScienceCollaboration you should phrase it carefully so that you believe you can establish or refute it. For example, a title like "vaccines are safe" is too vague to be established. TSScienceCollaboration deals with this by allowing a body of the statement where it can be spelled out in detail, specifying exactly what you hope to establish as considered "safe". Also, while it may be impossible to rigorously prove "anthropogenic global warming is heating the planet by .5 C per decade" it might be easier to establish "the preponderance of the evidence indicates anthropogenic global warming is heating the planet by .5° C per decade". Note though that this is not established merely by counting papers for and against. TSScienceCollaboration statements should provide rational arguments and 100 papers can be refuted by one rational argument.

When a TSScienceCollaboration topic is completely expanded, you should have a carefully worded statement that you actually know nobody can raise a rational dispute with. We believe that is better than having a vague grandiose statement that you believe but is likely wrong.

A statement is tentatively established if it has a tentatively established proof reply and every challenge reply has been tentatively refuted. If you feel the proofs are insufficient you may challenge the statement.

A statement is also tentatively established if no proof statements for it have been offered and every refuting statement targeting it has been tentatively refuted. This is to handle statements that are self-evident or contain their own proof in their body. If you don't believe such a statement is evident, you may challenge it asking for further proof.

If a statement is not tentatively established, then it is considered tentatively refuted.

Yes, a draft of your statement can be saved before posting it.

- On the top right of the Home Page screen, you will find the button "Add Topic". Click on this button to post a new topic.
- An Add New Topic Statement page will open up.
- Specify the statement category, statement title, statement details and source URLs. Select the topic sharing option as either Draft, Private, or Public.
- Click on the Post button to save the draft of the new topic or to Publish it. Once a draft has been saved, it can be accessed through the "My topics" link on the "My Account" drop down.

Featured topics are the topics which are being highlighted by those involved in the website.

Click on any of the categories (left of home page screen) to see all the topics under that category. Click on any of the topics to go to the topic's graph page.

To view the history of a topic being updated use the two gold buttons at the top of the graph on the right. Click on '1st' to select the first statement added to the graph and open two more gold buttons: left arrow and right arrow. Click the right arrow successively to see each statement added in sequence. Likewise, clicking the 'Last' button will select the last statement added to the graph and clicking the arrow button will successively select the next to last and so on.

There is also an "Edit History for Topic" tab at the very bottom of the graph page that will allow you to explore the history of when statements were added.

The topmost level on the graph view shows the topic title with the topic status. The graph gives a diagrammatic representation of different levels of supporting and refuting statements for a particular topic statement.

A statement box has two elements: - Pro or Con - All the pro statements are in green boxes and all the con statements are in red boxes. - Status - All the established statements are marked with a tick mark. All the refuted statements are marked with a cross.

When you hover the mouse pointer over a red or green box, in the graphic view, the title and body are displayed in the upper left corner of the window.

The selected users will receive an email invitation to the topic.

The Last Updated date field indicates the last time that the particular statement was edited.

A statement is tentatively established if it has a tentatively established proof reply and every challenge reply has been tentatively refuted. If you feel the proofs are insufficient you may challenge the statement.

A statement is also tentatively established if no proof statements for it have been offered and every refuting statement targeting it has been tentatively refuted. This is to handle statements that are self-evident or contain their own proof in their body. If you don't believe such a statement is evident, you may challenge it asking for further proof.

If a statement is not tentatively established, then it is considered tentatively refuted.

b) An Add New Topic Statement page will open up.

c) Specify the statement category, statement title, statement detail and Source URLs.

d) Click on Post button to post the new topic.

Clicking on the topic title will take you to the statement's graph page. The graph page for a topic statement displays the graph at the top and the topic statement detail information at the bottom.

Below the body of the topic statement you will find a reply button. Clicking on that will open a window and allow you to add either a proof or a challenge.

Similarly, you can select any node in the graph. This will display the title and body of the statement below the graph. A reply button at the bottom allows you to either add a proof or a refutation to that statement.

Sources lists the URL sources for a particular topic.

Sources (citations) can be viewed on the graph page below the topic statement details.

TSScienceCollaboration supports probabilistic ratings if switched to probability mode. This allows users to simply collaborate on constructing a Causal Bayes net modeling any question on all supplied evidence, and automatically computes the probabilities predicted using a fast Monte Carlo algorithm. You may make a number of observations about the world that are pertinent to whether a given hypothesis is true, such as " it was reported in the newspaper” and " the newspaper isn't always accurate” and "if that hypothesis is true some other thing I observed would be much more likely to hold than if it is false” . TSScienceCollaboration lets you combine your assessments and intuitions about different pieces of evidence into a rigorously calculated probability estimate.

The author of a topic can set it to probability mode by checking the "make this a probability graph” box right below the title on the add new topic window. In probability mode, contributors are asked to assign a "proposed belief", to the statements they add, between zero and one to reflect how much confidence they have that their statement either proves or refutes its target.

In probability mode, in addition to pro and con statements, users can add test statements which are like epidemiological tests that provide evidence favoring the truth or falsehood of their target. Given some observation claimed in the body of the test statement, the author of the test statement supplies a likelihood of the observation given that the target statement is true and the likelihood of the observation given that the target statement is false. According to Bayes law, this evidence multiplies the likelihood of the target statement by the ratio of the first number to the second.

For example, consider the medical test for breast cancer, It has a false positive probability of .12 ( meaning for a woman without the condition there is a .12 probability the test will show positive anyway) and it has a false negative probability of .27 ( meaning that if you do have the condition there is a .27 the test says you don't and thus only a .73 chance it says you do.). Thus a woman who has breast cancer is .73/.12=6 times as likely to get a positive test as one who doesn't. But since only 1/700 women have breast cancer, the likelihood of a woman with a positive test having breast cancer is only 6/700=.00857

TSScienceCollaboration probability mode allows you to represent this and calculate the likelihood of having breast cancer, using a test node with a likelihood given true target =.73 and a likelihood given false target of .12, and a prior node giving proof with expected belief 1/700. see https://TSScienceCollaboration.com/graph/Do%20I%20have%20cancer%20%20given%20a%20positive%20test/964/0/-1/-1/0/0#lnkNameGraph This simple example is taken from the discussion on pages 104-105 in Pearl, Judea. The Book of Why: The New Science of Cause and Effect. Basic Books. Kindle Edition.

TSScienceCollaboration then calculates the probability that the topic node is true ( the woman actually has cancer) by drawing random instances from the population conditioned on having a positive test. It does this by sampling instances with a 1/700 chance of having cancer, and then weighting the ones that actually have cancer by the factor .73 (the likelihood estimate given target true) and then weighting ones that don't by the factor . 12 ( likelihood estimate given target false). Then the likelihood that the topic node is true is given as the ratio of the total weight of positive instances divided by (the total weight of negative examples plus the total weight of positive examples) . This is a Monte Carlo calculation that gives as the expected value the same result as the Bayesian calculation.

On a general graph, TSScienceCollaboration generates 1000 instances ( or you can set it to 10,000 instances) by assigning a 1 to the leaves (nodes with no children) with probability their proposed belief. Then it goes up the graph, just as in the ordinary TSScienceCollaboration, assigning a 0 to any node that has a 1 challenge, or has no 1 proof and at least one 0 proof. Otherwise it assigns a 1 to each node with probability its proposed belief. Think of proofs as causes for their target, and refutations as causes the target is not true. Then it assigns a weight to each instance which is the product over all the 1 tests, of the probability they assign to their target being 1 rather than 0 (true rather than false) . Finally, the probability of each node, is the sum of the weights of all instances for which it is 1, divided by the sum of the weights of all instances. This amounts to sampling the possible events according to the causal model embodied in the graph and asking for what fraction the node is true.

TSScienceCollaboration thus allows you to build a big causal model with epidemiological tests bringing to bear all of the evidence on a given subject, and rapidly estimates the probability of the statements.