Version history

{
  "scope": "In vitro / ex vivo population imaging; near-infrared GEVIs Archon1 and nirButterfly",
  "claim_text": "Two leading near-infrared GEVIs, Archon1 and nirButterfly, each have complementary trade-offs in brightness, kinetics and signal amplitude — neither indicator currently combines all three properties optimally for mesoscopic in-vivo voltage imaging.",
  "raw_fields": {
    "n": 2,
    "doi": "10.1117/1.nph.11.2.024201",
    "claim": "Two leading near-infrared GEVIs, Archon1 and nirButterfly, each have complementary trade-offs in brightness, kinetics and signal amplitude — neither indicator currently combines all three properties optimally for mesoscopic in-vivo voltage imaging.",
    "cite_key": "Song2023b",
    "evidence": "Quantifies a present-day indicator-engineering bottleneck for the near-infrared voltage-imaging route that cluster_14 lists among emerging tools.",
    "effect_size": "nirButterfly is ~7× brighter than Archon1 under matched conditions, with faster kinetics; Archon1 has larger signals",
    "text_access": "abstract_only",
    "study_system": "In vitro / ex vivo population imaging; near-infrared GEVIs Archon1 and nirButterfly",
    "argument_role": "supporting",
    "replication_status": "single-study",
    "claim_source_sentence": "Neither GEVI characterized here surpasses in all three key parameters (brightness, kinetics, and sensitivity), so there is no unequivocal preference for one of the two.",
    "source_provenance_status": "non_substring_match",
    "replication_evidence_dois": [],
    "effect_size_source_sentence": "We found that nirButterfly shows seven-fold higher brightness than Archon1 under the same conditions and faster kinetics than Archon1 for population imaging without cellular resolution."
  },
  "section_id": "section_16",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_16_evidence_package.json",
  "effect_size": "nirButterfly is ~7× brighter than Archon1 under matched conditions, with faster kinetics; Archon1 has larger signals",
  "review_repo": "ComputationalReviewRecurrence",
  "section_ref": "wiki_page:computationalreviewrecurrence-16-synthesis",
  "source_kind": "review_finding",
  "source_path": "evidence/section_16_evidence_package.json",
  "source_refs": [
    "paper:paper-2481de1c0ae2"
  ],
  "source_span": "Neither GEVI characterized here surpasses in all three key parameters (brightness, kinetics, and sensitivity), so there is no unequivocal preference for one of the two.",
  "study_system": "In vitro / ex vivo population imaging; near-infrared GEVIs Archon1 and nirButterfly",
  "evidence_refs": [
    {
      "ref": "paper:paper-2481de1c0ae2"
    }
  ],
  "section_title": "16. Synthesis — which computational claims the mouse-cortex E→E empirical record actually supports, where the bottleneck observations are, and what an inhibition-free, single-species, basic-research analytic framing misses",
  "source_policy": {
    "mode": "public_source_pointer_with_short_context",
    "notes": [
      "Local review repositories are read-only inputs.",
      "SciDEX stores paper metadata, structured evidence, file pointers, and short citation contexts; it does not copy full review prose."
    ],
    "source_commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
    "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
  },
  "evidence_summary": "Quantifies a present-day indicator-engineering bottleneck for the near-infrared voltage-imaging route that cluster_14 lists among emerging tools.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "single-study",
  "review_package_ref": "analysis_bundle:ab-d9c479db9be9",
  "source_artifact_ref": "wiki_page:computationalreviewrecurrence-16-synthesis",
  "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_16_evidence_package.json",
  "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
  "created_by": "persona-jerome-lecoq-gbo-neuroscience",
  "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
}