Adding Columns

generating the insights you need in tabular adding a column after creating a project docid\ x6 8ly2ldfy0pt7nxsfco , tabular auto generates a results table with several columns depending on the project type and recipe used below is an output of an fda approved products search generated from the input i want to analyze drugs approved for renal cell carcinoma by default, this search recipe includes the drug name, brand name, manufacturer name, roa, application number, and product type columns, with values pulled directly from the fda labels to add new columns, click this will open the column selection interface column types tabular supports two column types deterministic data fields pulled directly from the data source with no language model processing these columns are suggested by default in the add column pane within tabular generative columns use reliant’s language model to extract specific data from source text, and are created via user prompts the user can enter any analytical prompt regarding their source document and receive precisely extracted data for each source in the table, forming a core part of tabular’s analysis capability default columns can be quickly found via the search bar at the top of the add column pane if you can’t find the specific information you need, a generative column can often help column generation tips more detail is often better! just like a human, the language model will search and synthesize information more precisely when it has more context on the request there is no restriction on generative column length use plain language when prompting the ai unlike when using traditional keyword search engines like google, it is beneficial to interact with the language model using prompts that mimic conversational language strong column example “is this product indicated for use in pediatric patients with renal cell carcinoma?” weak column example “pediatric patient approval” examples increase prompt efficacy just like a human coworker, reliant's model often performs better when given examples of the output you are looking for here are some sample prompts how many patients are included in this study? provide any descriptors of the patient population included (ex " 52 immunocompromised patients") (scientific literature project) what is the study type of this publication (ex observational study, meta analysis, modeling study, etc ) (scientific literature project) examples can be used to automatically format outputs tabular can generate outputs in specific format if asked! specify example outputs, and tell the model you are looking for a specific format in the prompt here are some formatting prompts generate a reference for this article in the following format alinam, s , timms, j a , dillon, r , et al (publication year) (journal name) (scientific literature project) what is the post treatment or post operative qmax at each specified outcome time periods? use the following format 10 2 ml/s, 1 mo; 13 5 ml/s, 6mo; 24 5 ml/s, 12 mo (scientific literature project) iterate with different phrasing to continually imrove extraction we strongly encourage users to iterate on generative column headers try a few wording variations side by side to compare which prompts most effectively extract information in the way you expect “n/a” result indicates lack of information the ai will return n/a if it cannot find information relevant to the question asked when asking a yes or no question, an n/a result is distinct from a no a no result indicates the ai has found information that is counter to the prompt, whereas n/a means no information was found to support nor deny the claim example generative ai columns describe the dosing for this product in detail, making sure to highlight if a site of care is mentioned (ex hospital, clinic, icu equipped facility) (fda label project) what clinical test measures are mentioned in the trial exclusion criteria? include specific numerical information (ex blood pressure > 140/90 mmhg) do not include age related exclusions (clinical trials project) list all drug names or molecules ending in "mab" that are listed as interventions in this trial (clinical trials project) does this abstract discuss wearable sensors or electronic data collection for hypertension patients? (scientific literature project) identify names of all clinical trials captured following this format trial name and nct code, comma separated (example "opal broaden, nct01877668") provide your answer as a simplified and concise list with no additional information (scientific literature project)