{"id":"W4402390402","doi":"10.1523/eneuro.0183-24.2024","title":"Electrical Stimulation for Stem Cell-Based Neural Repair: Zapping the Field to Action","year":2024,"lang":"en","type":"article","venue":"eNeuro","topic":"Neuroscience and Neural Engineering","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Krembil Foundation; University of Toronto; Toronto Rehabilitation Institute; University Health Network","funders":"Canada First Research Excellence Fund","keywords":"Stimulation; Action (physics); Field (mathematics); Neural stem cell; Stem cell; Neuroscience; Psychology; Physics; Cell biology; Biology; Mathematics; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002097241,0.0002791556,0.0002766454,0.0002179638,0.0002547576,0.0007790757,0.0003613726,0.000627496,0.002689892],"category_scores_gemma":[0.0003069879,0.00009728447,0.00025175,0.0001508038,0.0006634953,0.0008929555,0.0004504317,0.0009327328,0.0006778403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002296499,"about_ca_system_score_gemma":0.0002383312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001913837,"about_ca_topic_score_gemma":0.0003491298,"domain_scores_codex":[0.9999099,0.00001283152,0.000006083953,0.00001882308,0.00003393098,0.0000184332],"domain_scores_gemma":[0.9999205,0.00003230577,0.00001428621,0.000007808249,0.000009547918,0.00001554631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00033848,0.00005514038,0.0002107959,0.0004121193,0.00002582574,0.0002537679,0.0001755043,0.001642247,0.8933199,0.01823746,0.002000909,0.08332777],"study_design_scores_gemma":[0.0001255265,0.0009669368,0.001664019,0.0001472701,0.0000737365,0.001315454,0.0004001154,0.01400637,0.8887488,0.03468345,0.05781038,0.00005798235],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5362371,0.06658832,0.3350452,0.008524361,0.003719831,0.0001755208,0.0004477353,0.00138896,0.04787294],"genre_scores_gemma":[0.9571214,0.01210831,0.02146245,0.001128699,0.000272163,0.00006338927,0.00007373354,0.00008818977,0.007681772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002689892,"threshold_uncertainty_score":0.008998632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05511353701063888,"score_gpt":0.320300172447443,"score_spread":0.2651866354368042,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}