{"id":"W4308512866","doi":"10.1016/j.bpj.2022.11.007","title":"Characterizing spontaneous Ca2+ local transients in OPCs using computational modeling","year":2022,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Neuroscience and Neuropharmacology Research","field":"Neuroscience","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Biological system; Statistical physics; Biophysics; Computer science; Chemistry; Physics; Biology","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":[0.0001646096,0.0003027871,0.0003527379,0.0002191456,0.0003546856,0.0005697034,0.0006279818,0.0006672159,0.0008729154],"category_scores_gemma":[0.001058666,0.0002000032,0.0004070569,0.0002237639,0.0003373715,0.0006893281,0.0003137507,0.0005586649,0.0001299169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006627875,"about_ca_system_score_gemma":0.001000167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009785677,"about_ca_topic_score_gemma":0.006317986,"domain_scores_codex":[0.9999539,0.000006346712,0.00000269276,0.00001176616,0.00001261312,0.00001259452],"domain_scores_gemma":[0.9996971,0.0001928639,0.00002888312,0.00002378026,0.00003158293,0.00002587689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003782155,0.00004626196,0.00157149,0.00003030758,0.00001919196,0.0000881453,0.00004004066,0.982599,0.009690368,0.002850252,0.0002249729,0.002802009],"study_design_scores_gemma":[0.00000125845,0.000002562186,0.0001211456,5.234178e-7,0.000001117755,0.000005238765,0.000003070883,0.9991108,0.0003237853,0.0004066111,0.00002260208,0.000001352841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8723153,0.0001981611,0.1208745,0.0003901698,0.00003819347,0.00004105455,0.0002964511,0.0004516554,0.005394442],"genre_scores_gemma":[0.9940771,0.0000723603,0.005222574,0.00002950518,0.000006979748,0.00002531621,0.00007558443,0.00003586737,0.00045474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009785677,"threshold_uncertainty_score":0.01945746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0854936176055333,"score_gpt":0.3462080387681019,"score_spread":0.2607144211625685,"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."}}