By scispace.com
SciSpace is inactive right now!
This GPT3 for researchers and students can do hours worth of research in minutes.
| Field | Value |
|---|---|
| action_id | g-46c71962b413a1f9bcd1a4b26d5416b0f7e881f2 |
| domain | typeset.io |
| json_schema | {"openapi"=>"3.0.1", "info"=>{"version"=>"2.0.0", "title"=>"GPT Store API", "termsOfService"=>"https://example.com/terms/", "contact"=>{"email"=>"[email protected]", "url"=>"http://example.com/contact"}, "license"=>{"name"=>"Apache 2.0", "url"=>"http://www.apache.org/licenses/LICENSE-2.0.html"}, "x-logo"=>{"url"=>"https://redocly.github.io/openapi-template/logo.png"}, "description"=>"This is an API for a research paper backend. You can use this API to search for papers and get insights.\n"}, "servers"=>[{"url"=>"https://typeset.io"}], "paths"=>{"/api/v2/gpt/vector-search/"=>{"post"=>{"security"=>[{"api_key_auth"=>[]}], "tags"=>["Search"], "summary"=>"Vector search in papers", "description"=>"Get the vector search results when a search term is applied. This is used for the Global search.", "operationId"=>"vectorSearch", "requestBody"=>{"required"=>true, "content"=>{"application/json"=>{"schema"=>{"type"=>"object", "properties"=>{"search_term"=>{"type"=>"string", "description"=>"The search term to apply."}, "sort"=>{"type"=>"string", "description"=>"The sort order to apply.", "default"=>"relevance"}, "filter_info"=>{"type"=>"object", "description"=>"Filters to be applied on search", "properties"=>{"year"=>{"type"=>"string", "description"=>"papers published between specific years"}, "publication_type"=>{"type"=>"array", "items"=>{"type"=>"string"}}, "keywords"=>{"type"=>"object", "properties"=>{"include"=>{"type"=>"array", "items"=>{"type"=>"string"}}, "exclude"=>{"type"=>"array", "items"=>{"type"=>"string"}}}}, "published_in_journal"=>{"type"=>"array", "items"=>{"type"=>"string"}}, "published_in_conference"=>{"type"=>"array", "items"=>{"type"=>"string"}}}}, "page_info"=>{"type"=>"object", "description"=>"API pagination details. The pagination follows zero-based indexing. This means the first page is indexed as 0.", "properties"=>{"page"=>{"type"=>"integer", "description"=>"Page number to retrieve starting from zero"}, "page_size"=>{"type"=>"integer", "description"=>"Number of entities required per page"}}}}, "required"=>["search_term", "sort", "filter_info", "page_info"]}, "examples"=>{"example 1"=>{"summary"=>"Sample request on a query with no filters", "value"=>{"search_term"=>"How to increase immunity in men ?", "sort"=>"relevance", "filter_info"=>{}, "page_info"=>{"page"=>0, "page_size"=>5}}}, "example 2"=>{"summary"=>"Sample request on a query with filters", "value"=>{"search_term"=>"Papers on IC engines published between 2020 and 2023 ?", "sort"=>"relevance", "filter_info"=>{"has_pdf"=>true, "is_oa"=>true, "year"=>"2020,2023", "publication_type"=>[], "keywords"=>{}}, "page_info"=>{"page"=>0, "page_size"=>5}}}}}}}, "responses"=>{"200"=>{"$ref"=>"#/components/responses/Success"}}}}, "/api/v2/gpt/papers/context/"=>{"post"=>{"security"=>[{"api_key_auth"=>[]}], "tags"=>["Paper Info"], "summary"=>"Get Context for Papers", "description"=>"Get the context for the list of papers to add a column to the GPT search table.\n", "operationId"=>"getContextForPapers", "requestBody"=>{"required"=>true, "content"=>{"application/json"=>{"schema"=>{"$ref"=>"#/components/schemas/Request"}, "examples"=>{"200"=>{"summary"=>"Example of fetching context for papers", "description"=>"This is the example to fetch context for the list of papers.\n", "value"=>{"question"=>"What are Potential Biases", "entity_full_slugs"=>["effect-of-vitamin-d-on-cognitive-function-and-white-matter-2jho07ez4v", "cognitive-intraindividual-variability-and-white-matter-5az9sa8t9h"]}}}}}}, "responses"=>{"200"=>{"description"=>"OK", "content"=>{"application/json"=>{"schema"=>{"$ref"=>"#/components/schemas/Response"}, "examples"=>{"200"=>{"summary"=>"Success response for fetching context for papers", "description"=>"This is the success response for fetching context for the list of papers.\n", "value"=>{"data"=>[{"type"=>"object", "paper_slug"=>"cognitive-intraindividual-variability-and-white-matter-5az9sa8t9h", "context"=>["The intraindividual variability (IIV) of cognitive performance has been shown to increase with aging. While brain research has generally focused on mean performance, little is known about neural correlates of cognitive IIV. Nevertheless, some studies suggest that IIV relates more strongly than mean level of performance to the quality of white matter (WM). Our study aims to explore the relation between WM integrity and cognitive IIV by combining functional (fMRI) and structural (diffusion tensor imaging, DTI) imaging. Twelve young adults (aged 18–30 years) and thirteen older adults (61–82 years) underwent a battery of neuropsychological tasks, along with fMRI and DTI imaging. Their behavioral data were analyzed and correlated with the imaging data at WM regions of interest defined on the basis of (1) the fMRI-activated areas and (2) the Johns Hopkins University (JHU) WM tractography atlas. For both methods, fractional anisotropy, along with the mean, radial, and axial diffusivity parameters, was computed. In accord with previous studies, our results showed that the DTI parameters were more related to IIV than to mean performance. Results also indicated that age differences in the DTI parameters were more pronounced in the regions activated primarily by young adults during a choice reaction-time task than in those also activated in older adults."]}, {"type"=>"object", "paper_slug"=>"effect-of-vitamin-d-on-cognitive-function-and-white-matter-2jho07ez4v", "context"=>["Aim To examine the effect of vitamin D level on cognitive function and white matter hyperintensity (WMH) in patients with mild Alzheimer's disease (AD). Methods We recruited patients with mild AD, and carried out clinical interviews, neuropsychological assessments, laboratory tests and brain magnetic resonance imaging. Results In total, 146 patients"]}]}}}}}}}}}}, "components"=>{"securitySchemes"=>{"api_key_auth"=>{"type"=>"apiKey", "in"=>"header", "name"=>"Authorization"}}, "schemas"=>{"Journal"=>{"type"=>"object", "title"=>"Journal", "properties"=>{"display_name"=>{"description"=>"The display name of the journal.", "type"=>"string"}, "official_page"=>{"description"=>"The official page of the journal.", "type"=>"string"}, "issn"=>{"description"=>"The ISSN of the journal.", "type"=>"string"}, "alias"=>{"description"=>"The alias of the journal.", "type"=>"array", "items"=>{"type"=>"string"}}, "id"=>{"description"=>"The unique ID of the journal.", "type"=>"integer"}, "slug"=>{"description"=>"The slug of the journal.", "type"=>"string"}, "unique_id"=>{"description"=>"The unique ID of the journal.", "type"=>"string"}, "full_slug"=>{"description"=>"The full slug of the journal.", "type"=>"string"}}}, "Author"=>{"type"=>"object", "title"=>"Author", "properties"=>{"display_name"=>{"description"=>"The display name of the author.", "type"=>"string"}, "id"=>{"description"=>"The unique ID of the author.", "type"=>"integer"}, "slug"=>{"description"=>"The slug of the author.", "type"=>"string"}, "unique_id"=>{"description"=>"The unique ID of the author.", "type"=>"string"}, "full_slug"=>{"description"=>"The full slug of the author.", "type"=>"string"}}}, "Request"=>{"type"=>"object", "title"=>"Get Context For a question on List of Papers", "properties"=>{"question"=>{"type"=>"string", "description"=>"The question for the column asked by the user.\n"}, "entity_full_slugs"=>{"type"=>"array", "items"=>{"type"=>"string"}, "description"=>"The full slugs of the papers."}}, "required"=>["question", "entity_full_slugs"]}, "Response"=>{"type"=>"object", "title"=>"Generic Response to get context for a list of papers", "properties"=>{"data"=>{"type"=>"array", "items"=>{"type"=>"object", "properties"=>{"paper_slug"=>{"type"=>"string", "description"=>"The full slug of the paper."}, "context"=>{"type"=>"array", "items"=>{"type"=>"string"}, "description"=>"The context for the paper."}}}, "description"=>"The context data for the papers. You should take into consideration the original language in which the user asked the question while consuming this endpoint. The context data is always in english, so you should translate this response to the original language of the user question and generate the final response in the same language in which user asked the question.\n"}}}}, "responses"=>{"Success"=>{"description"=>"Vector Search Response", "content"=>{"application/json"=>{"schema"=>{"type"=>"object", "properties"=>{"total"=>{"type"=>"integer", "description"=>"Total number of search results"}, "data"=>{"type"=>"array", "items"=>{"type"=>"object", "properties"=>{"id"=>{"type"=>"integer", "description"=>"The unique ID of the paper."}, "title"=>{"type"=>"string", "description"=>"The title of the paper."}, "is_archived"=>{"type"=>"boolean", "description"=>"Whether the paper is archived."}, "full_slug"=>{"type"=>"string", "description"=>"The full slug of the paper."}, "journal"=>{"$ref"=>"#/components/schemas/Journal"}, "conference_series"=>{"type"=>"object", "properties"=>{"display_name"=>{"type"=>"string", "description"=>"The display name of the conference series."}, "official_page"=>{"type"=>"string", "description"=>"The official page of the conference series."}, "id"=>{"type"=>"integer", "description"=>"The unique ID of the conference series."}, "slug"=>{"type"=>"string", "description"=>"The slug of the conference series."}, "unique_id"=>{"type"=>"string", "description"=>"The unique ID of the conference series."}, "full_slug"=>{"type"=>"string", "description"=>"The full slug of the conference series."}}}, "date"=>{"type"=>"string", "description"=>"The date of the paper."}, "is_oa"=>{"type"=>"boolean", "description"=>"Whether the paper is open access."}, "publication_type"=>{"type"=>"string", "description"=>"The publication type of the paper."}, "doi"=>{"type"=>"string", "description"=>"The DOI of the paper."}, "abstract"=>{"type"=>"string", "description"=>"The abstract of the paper."}, "authors"=>{"type"=>"object", "properties"=>{"total"=>{"type"=>"integer", "description"=>"Total number of authors"}, "data"=>{"type"=>"array", "items"=>{"$ref"=>"#/components/schemas/Author"}}}}}}}}}}}}}}} |
| auth | {"type":"service_http","instructions":"","authorization_type":"custom","verification_tokens":{},"custom_auth_header":"Authorization"} |
| privacy_policy_url | https://typeset.io/t/security-commitment/ |
| Capabilitiy | Function | Tools |
|---|---|---|
| Code Interpreter / Data Analysis | Execute Python code for automation, calculations, and data analysis. | Python |
| Web Browsing | Real-Time Access and search the internet for information, articles, and data. | Browser |
| DALLE•E | Generate unique images based on textual descriptions provided. | Dalle |
Currently, this GPTs is not free and is available exclusively to ChatGPT Plus users.
Yes, besides requiring a ChatGPT Plus membership, if you use the GPT-4 model (with DALL·E, browsing, and data analysis), the limit is 25 'GPTs' messages / 3 hours, More limited than normal 40 GPT4 responses per 3 hours,
The enterprise version of ChatGPT is, 100 GPT-4 messages per 3 hours.
SciSpace is publicly available in the upcoming OpenAI's GPT Store, making it widely accessible to anyone interested in using this advanced ChatGPT.
SciSpace is created by scispace.com, and we have discovered only this one GPTs created by scispace.com.
no, we found no file uploaded. You can check the function section to see if there are other unique features. If not, this GPTs is just a simple prompt engineering, and its knowledge base is synchronized with the general ChatGPT, latest training up to April 2023.
No, only scispace.com can edit this GPTs. They can configure and update GPTs through GPT Builder at https://chat.openai.com/gpts/editor/g-NgAcklHd8. The last modification date of SciSpace was 2024-06-02 21:00:42 UTC.
Yes, conversations with SciSpace will be recorded. OpenAI keeps these records, and you can share your conversations via a link. Refer to OpenAI's user privacy and data security policies for more information.
Yes, if scispace.com selected "Use conversation data in your GPT to improve our models" (in the GPTs Configure pages of Additional Settings), it means your conversations will be used for training and will influence this GPT AI agent.
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