Family Coverage

Element Details

{
  "atoms": [
    {
      "_inventory_only": true,
      "atom_id": "L01-MML-LEARNERPREFERE",
      "atom_name": "Student Preference Data Collection",
      "atomic_definition": "Evaluates whether the system possesses a record of the student\u0027s stated (explicit) or demonstrated (implicit) preference for specific instructional modalities, creating the data basis for agency-oriented adaptation.",
      "definition": "Evaluates whether the system possesses a record of the student\u0027s stated (explicit) or demonstrated (implicit) preference for specific instructional modalities, creating the data basis for agency-oriented adaptation.",
      "family_code": "MML",
      "family_name": "MML",
      "internal_id": "MML01",
      "source_file": "L01-MML-LEARNERPREFERE.json",
      "weight_estimation": {}
    }
  ],
  "compounds": [],
  "constructs": [],
  "elements": [
    {
      "_inventory_only": true,
      "aggregation_method": {},
      "atom_ids": [],
      "element_id": "E-L01-CONTEXT-BRIDGE",
      "element_name": "E-L01-CONTEXT-BRIDGE",
      "family_code": "CTX",
      "family_name": "CTX",
      "output_contract": {
        "returns": "contextual_constraints",
        "schema": {
          "adaptation_flags": {
            "enable_offline_fallback": "boolean",
            "extend_timeouts": "boolean",
            "reduce_cognitive_load": "boolean",
            "simplify_interface": "boolean"
          },
          "confidence": "number:0-1",
          "element_id": "string",
          "modality_constraints": {
            "allowed_modalities": "array:string",
            "bandwidth_tier": "enum:2G|3G|4G|5G",
            "forbidden_modalities": "array:string",
            "max_session_length_minutes": "number",
            "offline_mode_required": "boolean"
          },
          "session_viability": {
            "blocker_details": "array:string",
            "constraint_severity": "enum:NONE|MINOR|MODERATE|CRITICAL",
            "viable": "boolean"
          },
          "source_context_vector_ref": "string",
          "state_assessment_modifiers": {
            "attention_constraint": "enum:NORMAL|REDUCED|SEVERELY_LIMITED",
            "disruption_recovery_mode": "boolean",
            "emotional_safety_caution": "boolean",
            "time_constraint_minutes": "number"
          },
          "timestamp": "ISO8601"
        }
      },
      "purpose": "Bridge the gap between ecological context (CLEA) and student state assessment (LOPA). Provides context-informed constraints that modulate interpretation of current-state evidence."
    },
    {
      "_inventory_only": true,
      "aggregation_method": {
        "min_atoms_required": 3,
        "missing_handling": "exclude_from_aggregate",
        "strategy": "weighted_mean",
        "weights_source": "atom_confidence"
      },
      "atom_ids": [
        "C1",
        "C10",
        "C3",
        "C4",
        "C6",
        "C7",
        "C8",
        "C9"
      ],
      "element_id": "E-L01-CS-BUNDLE",
      "element_name": "E-L01-CS-BUNDLE",
      "family_code": "CS",
      "family_name": "CS",
      "output_contract": {
        "returns": "evidence_bundle",
        "schema": {
          "aggregate_confidence": "number:0-1",
          "aggregate_score": "number:0-99",
          "element_id": "string",
          "family_code": "string",
          "scores": [
            {
              "atom_id": "string",
              "confidence": "number:0-1",
              "score": "number:0-99"
            }
          ],
          "timestamp": "ISO8601"
        }
      },
      "purpose": "Aggregate contextual evidence including task constraints, feedback topology, error cost structure, noise-to-signal ratio, scaffolding configuration, and curriculum path dependencies."
    },
    {
      "_inventory_only": true,
      "aggregation_method": {
        "min_atoms_required": 2,
        "missing_handling": "exclude_from_aggregate",
        "strategy": "weighted_mean",
        "weights_source": "atom_confidence"
      },
      "atom_ids": [
        "E1",
        "E2",
        "E3",
        "E6",
        "E8"
      ],
      "element_id": "E-L01-EF-BUNDLE",
      "element_name": "E-L01-EF-BUNDLE",
      "family_code": "EF",
      "family_name": "EF",
      "output_contract": {
        "returns": "evidence_bundle",
        "schema": {
          "aggregate_confidence": "number:0-1",
          "aggregate_score": "number:0-99",
          "element_id": "string",
          "family_code": "string",
          "scores": [
            {
              "atom_id": "string",
              "confidence": "number:0-1",
              "score": "number:0-99"
            }
          ],
          "timestamp": "ISO8601"
        }
      },
      "purpose": "Aggregate error and feedback evidence including prediction error sensitivity, error attribution, surprise tolerance, hypothesis revision, and feedback interpretability."
    },
    {
      "_inventory_only": true,
      "aggregation_method": {
        "min_atoms_required": 0,
        "missing_handling": "exclude_from_aggregate",
        "strategy": "weighted_mean",
        "weights_source": "atom_confidence"
      },
      "atom_ids": [],
      "element_id": "E-L01-GEN-BUNDLE",
      "element_name": "E-L01-GEN-BUNDLE",
      "family_code": "GEN",
      "family_name": "GEN",
      "output_contract": {
        "returns": "evidence_bundle",
        "schema": {
          "aggregate_confidence": "number:0-1",
          "aggregate_score": "number:0-99",
          "element_id": "string",
          "family_code": "string",
          "scores": [
            {
              "atom_id": "string",
              "confidence": "number:0-1",
              "score": "number:0-99"
            }
          ],
          "timestamp": "ISO8601"
        }
      },
      "purpose": "Aggregate general system evidence for cross-family coordination. Reserved for audit, control, and provenance atoms."
    },
    {
      "_inventory_only": true,
      "aggregation_method": {
        "min_atoms_required": 3,
        "missing_handling": "exclude_from_aggregate",
        "strategy": "weighted_mean",
        "weights_source": "atom_confidence"
      },
      "atom_ids": [
        "A1",
        "A10",
        "A2",
        "A3",
        "A4",
        "A5",
        "A6",
        "A7",
        "A8",
        "A9"
      ],
      "element_id": "E-L01-MAI-BUNDLE",
      "element_name": "E-L01-MAI-BUNDLE",
      "family_code": "MAI",
      "family_name": "MAI",
      "output_contract": {
        "returns": "evidence_bundle",
        "schema": {
          "aggregate_confidence": "number:0-1",
          "aggregate_score": "number:0-99",
          "element_id": "string",
          "family_code": "string",
          "scores": [
            {
              "atom_id": "string",
              "confidence": "number:0-1",
              "score": "number:0-99"
            }
          ],
          "timestamp": "ISO8601"
        }
      },
      "purpose": "Aggregate motivational-affective evidence including self-efficacy, stress reactivity, frustration tolerance, curiosity, and belonging signals."
    },
    {
      "_inventory_only": true,
      "aggregation_method": {
        "min_atoms_required": 3,
        "missing_handling": "exclude_from_aggregate",
        "strategy": "weighted_mean",
        "weights_source": "atom_confidence"
      },
      "atom_ids": [
        "M1",
        "M2",
        "M4",
        "M5",
        "M6",
        "M7",
        "M8",
        "M9"
      ],
      "element_id": "E-L01-MC-BUNDLE",
      "element_name": "E-L01-MC-BUNDLE",
      "family_code": "MC",
      "family_name": "MC",
      "output_contract": {
        "returns": "evidence_bundle",
        "schema": {
          "aggregate_confidence": "number:0-1",
          "aggregate_score": "number:0-99",
          "element_id": "string",
          "family_code": "string",
          "scores": [
            {
              "atom_id": "string",
              "confidence": "number:0-1",
              "score": "number:0-99"
            }
          ],
          "timestamp": "ISO8601"
        }
      },
      "purpose": "Aggregate metacognitive evidence including goal clarity, strategy selection, monitoring resolution, planning horizon, and help-seeking calibration."
    },
    {
      "_inventory_only": true,
      "aggregation_method": {
        "min_atoms_required": 1,
        "missing_handling": "flag_as_unknown",
        "strategy": "direct_passthrough",
        "weights_source": "atom_confidence"
      },
      "atom_ids": [
        "MML01"
      ],
      "element_id": "E-L01-MML-BUNDLE",
      "element_name": "E-L01-MML-BUNDLE",
      "family_code": "MML",
      "family_name": "MML",
      "output_contract": {
        "downstream_handoff": {
          "handoff_field": "modality_preference_profile",
          "target_agent": "MSA",
          "target_layer": "L05"
        },
        "returns": "evidence_bundle",
        "schema": {
          "aggregate_confidence": "number:0-1",
          "aggregate_score": "number:0-99",
          "element_id": "string",
          "family_code": "string",
          "modality_preference_profile": "object",
          "scores": [
            {
              "atom_id": "string",
              "confidence": "number:0-1",
              "score": "number:0-99"
            }
          ],
          "timestamp": "ISO8601"
        }
      },
      "purpose": "Aggregate multimodal preference evidence for personalised modality selection. Outputs feed to L05 MSA for modality optimization."
    },
    {
      "_inventory_only": true,
      "aggregation_method": {},
      "atom_ids": [],
      "element_id": "E-L01-PER-BRIDGE",
      "element_name": "E-L01-PER-BRIDGE",
      "family_code": "PER",
      "family_name": "PER",
      "output_contract": {
        "returns": "personality_state_modifiers",
        "schema": {
          "baselines": {
            "collaboration_fit": "number:0-99",
            "exploration_propensity": "number:0-99",
            "self_regulation_baseline": "number:0-99",
            "stress_sensitivity_baseline": "number:0-99"
          },
          "confidence": "number:0-1",
          "element_id": "string",
          "preferences": {
            "feedback_modality_preference": "enum:INTERACTIVE|ASYNCHRONOUS",
            "novelty_tolerance": "enum:HIGH|MODERATE|LOW",
            "social_engagement_preference": "enum:COLLABORATIVE|FLEXIBLE|SOLITARY"
          },
          "source_profile": "personality_profile_signature_ref",
          "thresholds": {
            "critique_sensitivity": "number:0-99",
            "frustration_threshold_modifier": "number:0-99"
          },
          "timestamp": "ISO8601"
        }
      },
      "purpose": "Bridge the gap between stable personality traits and dynamic learning state assessment. Provides personality-informed baselines that modulate interpretation of current-state evidence."
    },
    {
      "_inventory_only": true,
      "aggregation_method": {
        "min_atoms_required": 2,
        "missing_handling": "exclude_from_aggregate",
        "strategy": "weighted_mean",
        "weights_source": "atom_confidence"
      },
      "atom_ids": [
        "P1",
        "P2",
        "P3",
        "P4",
        "P5",
        "P8",
        "P9"
      ],
      "element_id": "E-L01-PRC-BUNDLE",
      "element_name": "E-L01-PRC-BUNDLE",
      "family_code": "PRC",
      "family_name": "PRC",
      "output_contract": {
        "returns": "evidence_bundle",
        "schema": {
          "aggregate_confidence": "number:0-1",
          "aggregate_score": "number:0-99",
          "element_id": "string",
          "family_code": "string",
          "scores": [
            {
              "atom_id": "string",
              "confidence": "number:0-1",
              "score": "number:0-99"
            }
          ],
          "timestamp": "ISO8601"
        }
      },
      "purpose": "Aggregate processing capacity evidence including working memory availability, processing speed, cognitive flexibility, interference susceptibility, cognitive fatigue, and automaticity."
    },
    {
      "_inventory_only": true,
      "aggregation_method": {
        "min_atoms_required": 3,
        "missing_handling": "exclude_from_aggregate",
        "strategy": "weighted_mean",
        "weights_source": "atom_confidence"
      },
      "atom_ids": [
        "R1",
        "R10",
        "R3",
        "R4",
        "R6",
        "R7",
        "R8",
        "R9"
      ],
      "element_id": "E-L01-REP-BUNDLE",
      "element_name": "E-L01-REP-BUNDLE",
      "family_code": "REP",
      "family_name": "REP",
      "output_contract": {
        "returns": "evidence_bundle",
        "schema": {
          "aggregate_confidence": "number:0-1",
          "aggregate_score": "number:0-99",
          "element_id": "string",
          "family_code": "string",
          "scores": [
            {
              "atom_id": "string",
              "confidence": "number:0-1",
              "score": "number:0-99"
            }
          ],
          "timestamp": "ISO8601"
        }
      },
      "purpose": "Aggregate representational evidence including concept granularity, misconceptions, abstraction level, schema connectivity, procedural representation, and episodic trace density."
    },
    {
      "_inventory_only": true,
      "aggregation_method": {
        "min_atoms_required": 3,
        "missing_handling": "exclude_from_aggregate",
        "strategy": "weighted_mean",
        "weights_source": "atom_confidence"
      },
      "atom_ids": [
        "T1",
        "T10",
        "T2",
        "T3",
        "T4",
        "T5",
        "T6",
        "T7",
        "T8",
        "T9"
      ],
      "element_id": "E-L01-TLD-BUNDLE",
      "element_name": "E-L01-TLD-BUNDLE",
      "family_code": "TLD",
      "family_name": "TLD",
      "output_contract": {
        "returns": "evidence_bundle",
        "schema": {
          "aggregate_confidence": "number:0-1",
          "aggregate_score": "number:0-99",
          "element_id": "string",
          "family_code": "string",
          "scores": [
            {
              "atom_id": "string",
              "confidence": "number:0-1",
              "score": "number:0-99"
            }
          ],
          "timestamp": "ISO8601"
        }
      },
      "purpose": "Aggregate temporal dynamics evidence including consolidation efficiency, forgetting rate, spacing sensitivity, retrieval strength, automatization trajectory, and transfer latency."
    }
  ],
  "metadata": {
    "agent": "lopa",
    "generated_at": "",
    "generator": "LOPA Operator Inference v3",
    "layer": "L01",
    "synced_at": "2026-04-11T17:56:31.995715+00:00"
  },
  "summary": {
    "compounds": 0,
    "constructs": 0,
    "duplicates_resolved": 0,
    "total_atoms": 1,
    "total_elements": 11,
    "validation_passed": true
  },
  "validation": {
    "family_coverage": {
      "MML": [
        "CP-CS",
        "CP-LODA",
        "CP-LOPA"
      ]
    },
    "issues": [],
    "passed": true
  }
}