Enum: AgentTypeEnum

Permissible Values

Value	Meaning	Description
manual_agent	None	A human agent who is responsible for generating a statement of knowledge. The human may utilize computationally generated information as evidence for the resulting knowledge, but the human is the one who ultimately interprets/reasons with this evidence to produce a statement of knowledge.
automated_agent	None	An automated agent, typically a software program or tool, that is responsible for generating a statement of knowledge. Human contribution to the knowledge creation process ends with the definition and coding of algorithms or analysis pipelines that get executed by the automated agent.
data_analysis_pipeline	None	An automated agent that executes an analysis workflow over data and reports the direct results of the analysis. These typically report statistical associations/correlations between variables in the input dataset, and do not interpret/infer broader conclusions from associations the analysis reveals in the data.
computational_model	None	An automated agent that generates knowledge statements (typically predictions) based on rules/logic explicitly encoded in an algorithm (e.g. heuristic models, supervised classifiers), or learned from patterns observed in data (e.g. ML models, unsupervised classifiers).
text_mining_agent	None	An automated agent that uses Natural Language Processing to recognize concepts and/or relationships in text, and report them using formally encoded semantics (e.g. as an edge in a knowledge graph).
image_processing_agent	None	An automated agent that processes images to generate textual statements of knowledge derived from the image and/or expressed in text the image depicts (e.g. via OCR).
manual_validation_of_automated_agent	None	A human agent reviews and validates/approves the veracity of knowledge that is initially generated by an automated agent.
not_provided	None	The agent type is not provided, typically because it cannot be determined from available information if the agent that generated the knowledge is manual or automated.

Slots constrained by this enum

Name
agent_type

LinkML Source

name: AgentTypeEnum
in_subset:
- translator_minimal
from_schema: https://w3id.org/biolink/biolink-model
permissible_values:
  manual_agent:
    text: manual_agent
    description: A human agent who is responsible for generating a statement of knowledge.
      The human may utilize computationally generated information as evidence for
      the resulting knowledge,  but the human is the one who ultimately interprets/reasons
      with  this evidence to produce a statement of knowledge.
  automated_agent:
    text: automated_agent
    description: An automated agent, typically a software program or tool, that is  responsible
      for generating a statement of knowledge. Human contribution  to the knowledge
      creation process ends with the definition and coding of algorithms or analysis
      pipelines that get executed by the automated agent.
  data_analysis_pipeline:
    text: data_analysis_pipeline
    description: An automated agent that executes an analysis workflow over data and  reports
      the direct results of the analysis. These typically report  statistical associations/correlations
      between variables in the input dataset, and do not interpret/infer broader conclusions
      from associations the analysis reveals in the data.
    is_a: automated_agent
    notes:
    - If an analysis pipeline includes any rules for generating broader  conclusions
      based on the dataset-specific statistical correlations it calculates (e.g. create
      a 'treats' edge when the analysis reveals a  drug-disease correlation in the
      data with statistical scores that meet a  certain threshold) - we would consider
      this agent to be a Computational Model rather than just a Data Analysis Pipeline.
  computational_model:
    text: computational_model
    description: An automated agent that generates knowledge statements (typically
      predictions) based on rules/logic explicitly encoded in an algorithm (e.g. heuristic
      models, supervised classifiers), or learned from patterns  observed in data
      (e.g. ML models, unsupervised classifiers).
    is_a: automated_agent
    notes:
    - The bar is quite low relatively for what is considered to be a  ‘computational
      model’ by our definition. Even agents/tools that apply  simple rules or logic
      to the output of an ingest or analysis pipeline to allow for a stronger or more
      general conclusion to be stated can  qualify an agent as a model. For example,
      an ingest pipeline that applies rules to its ingest of  clinical trials data
      to create a 'treats' prediction edge when the  source reports a drug to be in
      phase 2 or 3 trials represents a computational model because it is automatically
      drawing a stronger conclusion than the source reports, based on logic encoded
      in the ingest pipeline. Similarly, a data analysis pipeline that is extended
      with rules to  automatically generate broader conclusions based on dataset-specific
      statistical correlations (e.g. create a 'treats' edge when the analysis reveals
      a drug-disease correlation in the data with statistical scores  that meet a
      certain threshold), would also qualify as a computational  model by our definition.
  text_mining_agent:
    text: text_mining_agent
    description: An automated agent that uses Natural Language Processing to recognize
      concepts and/or relationships in text, and report them using formally encoded
      semantics (e.g. as an edge in a knowledge graph).
    is_a: automated_agent
    notes:
    - The original statement in the source text is typically made by a human /  manual
      agent, but if a specific encoding of this knowledge is produced by a text-mining
      tool, it has an agent_type of 'text_mining_agent'. Examples of text mining agents
      include SemmedDB, and the Translator Text-Mining Knowledge Provider. Note that
      text-mining tools are prone to erroneous interpretation of  concepts and relationships,
      and can fail to provide important details  about the context in which the original
      knowledge was reported - so users should always consult the source text for
      a text-mined statement to assess its veracity and relevance.
  image_processing_agent:
    text: image_processing_agent
    description: An automated agent that processes images to generate textual statements
      of  knowledge derived from the image and/or expressed in text the image  depicts
      (e.g. via OCR).
    is_a: automated_agent
  manual_validation_of_automated_agent:
    text: manual_validation_of_automated_agent
    description: A human agent reviews and validates/approves the veracity of knowledge  that
      is initially generated by an automated agent.
    notes:
    - This term applies when a human was only involved in evaluating the veracity
      of a knowledge statement that was generated by an automated agent. It is  important
      to indicate when such manual review has occurred, because it can give a user
      more confidence in an automated statement.
  not_provided:
    text: not_provided
    description: The agent type is not provided, typically because it cannot be determined
      from available information if the agent that generated the knowledge is  manual
      or automated.