ECR 000003 EXP002 P001B bullets

packet_id: ECR-000003-EXP002-P001B experiment_id: EXP-002 variant_id: P001B artifact_family_id: P001 recognition_condition: bullets blinded_artifact_id: BR-EXP002-P001

blinded_procedural_content:

• start from an unresolved issue
• generate multiple possible paths
• gather a differentiating input
• reassess the paths using that input
• if separation remains weak, repeat the gather and reassess cycle
• end when one path is selected or continuation is no longer justified

instructions:

You are participating in a blinded procedural observation study.

Your task is to recover procedural observations from the packet.

Your objective is faithful extraction, not normalization.

Do not evaluate the theory behind the study.

Do not evaluate Framework Engineering.

Do not update hypotheses.

Do not redesign, critique, optimize, or extend the procedure.

If recognition is unavoidable, record it only in the recognized_artifact field.

Do not use prior knowledge of a recognized artifact to fill in structure beyond what is reasonably supported by the packet.

Base your response only on the packet content and reasonable procedural implications of that content.

Do not invent unsupported procedural structure.

If multiple procedural decompositions are equally reasonable, do not choose one simply to make the representation cleaner. Record the ambiguity explicitly.

Prefer reporting multiple plausible interpretations over collapsing them into a single interpretation when the packet supports more than one reading.

For graph or table packets, do not infer domain terminology unless it is present in the packet.

Record uncertainty explicitly.

Return exactly one valid JSON object matching the supplied schema.

Do not include markdown.

json_schema:

{
  "packet_id": "",
  "experiment_id": "",
  "variant_id": "",
  "artifact_family_id": "",
  "recognition_condition": "",
  "blinded_artifact_id": "",
  "recognized_artifact": "",
  "structural_layer": {"entry_conditions":[{"value":"","support_level":"","source_text":"","ambiguity":""}],"exit_conditions":[{"value":"","support_level":"","source_text":"","ambiguity":""}],"required_steps":[{"value":"","support_level":"","source_text":"","ambiguity":""}],"optional_steps":[{"value":"","support_level":"","source_text":"","ambiguity":""}],"loops":[{"value":"","support_level":"","source_text":"","ambiguity":""}],"branches":[{"value":"","support_level":"","source_text":"","ambiguity":""}],"termination_conditions":[{"value":"","support_level":"","source_text":"","ambiguity":""}],"control_flow_shape":""},
  "primitive_layer": {"primitive_sequence":[],"transitions":[],"dominant_primitive":"","candidate_missing_primitives":[]},
  "constraint_layer": {"invariants":[{"value":"","support_level":"","source_text":"","ambiguity":""}],"preconditions":[{"value":"","support_level":"","source_text":"","ambiguity":""}],"postconditions":[{"value":"","support_level":"","source_text":"","ambiguity":""}],"stopping_criteria":[{"value":"","support_level":"","source_text":"","ambiguity":""}],"validity_conditions":[{"value":"","support_level":"","source_text":"","ambiguity":""}]},
  "representation_layer": {"procedural_ast":{},"natural_language_summary":"","canonical_summary":"","ambiguities":[{"location":"","description":"","plausible_interpretations":[],"effect_on_extraction":""}]},
  "recognition_analysis": {"recognition_occurred":"","recognition_basis":"","domain_terms_introduced":[],"prior_knowledge_leakage_risk":""},
  "confidence": {"structural_layer":"","primitive_layer":"","constraint_layer":"","representation_layer":"","recognition_analysis":"","overall":""},
  "notes": ""
}