{"id":"W4391214682","doi":"10.1093/imamat/hxae002","title":"A bubble model for the gating of Kv channels","year":2023,"lang":"en","type":"article","venue":"IMA Journal of Applied Mathematics","topic":"Electrochemical Analysis and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Gating; Bubble; Randomness; Physics; Channel (broadcasting); Work (physics); Mechanics; Voltage; Statistical physics; Mathematics; Computer science; Thermodynamics; Quantum mechanics; Biophysics; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003285623,0.00008600292,0.0002552704,0.00003707904,0.00007951759,0.00001945802,0.0002975671,0.00004567172,0.00002433048],"category_scores_gemma":[0.00006220432,0.00005470354,0.0001815648,0.0002041054,0.00003733571,0.00002137799,0.00003694502,0.000134537,0.000006250548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001572651,"about_ca_system_score_gemma":0.00003637963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.729158e-7,"about_ca_topic_score_gemma":2.088262e-7,"domain_scores_codex":[0.9990306,8.083733e-7,0.0005275307,0.00006804247,0.0002168636,0.0001560841],"domain_scores_gemma":[0.9986302,0.0004648893,0.0005539202,0.0001865734,0.0001237692,0.00004059672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001435446,0.0001008646,8.198684e-7,0.0003102755,0.000148607,2.475015e-7,0.0010408,0.01288449,0.9591562,0.02312273,0.00169624,0.001524363],"study_design_scores_gemma":[0.0001969899,0.000005823746,1.068111e-7,0.00004462542,0.0001246862,0.000004606502,0.0005923195,0.5216787,0.3623053,0.1147745,0.0002204258,0.0000519743],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4828387,0.0002296154,0.5054435,0.001326188,0.00002713694,0.0002774101,0.00003342488,0.00005862672,0.009765384],"genre_scores_gemma":[0.9577121,0.00007250009,0.0415361,0.00003335398,0.0001546899,0.00004616065,0.000004020256,0.00002271405,0.0004183374],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.596851,"threshold_uncertainty_score":0.2230746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03218658211786379,"score_gpt":0.2816086029106267,"score_spread":0.2494220207927629,"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."}}