{"id":"W2990393593","doi":"10.1149/2.0731915jes","title":"Flux: Software for Analysing SECM Data","year":2019,"lang":"en","type":"article","venue":"Journal of The Electrochemical Society","topic":"Electrochemical Analysis and Applications","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Research Council Canada","keywords":"Workflow; Python (programming language); Software; Scripting language; Disk formatting; Computer science; Integrator; Flux (metallurgy); Normalization (sociology); Computational science; Materials science; Electrical engineering; Voltage; Programming language; Operating system; Engineering; Database","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":[0.0003032261,0.0001543221,0.0003483333,0.00001095289,0.0001375837,0.00004711122,0.001552767,0.0001530015,0.000222124],"category_scores_gemma":[0.0002483754,0.00009929371,0.0007945874,0.0003861061,0.00005028508,0.0001214347,0.0002239651,0.0005964871,0.000008086076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001524133,"about_ca_system_score_gemma":0.0001321062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000125586,"about_ca_topic_score_gemma":6.189289e-7,"domain_scores_codex":[0.9985421,0.00000965076,0.0004795819,0.0002650034,0.000365156,0.0003385008],"domain_scores_gemma":[0.9981303,0.0002681975,0.0004864927,0.0007902321,0.000227419,0.00009739681],"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":[0.00002134416,0.00007364531,0.0007764311,0.00004768307,0.0003499764,5.894286e-8,0.00002670287,0.000003148376,0.9871849,0.0000459402,0.01094843,0.0005217742],"study_design_scores_gemma":[0.0004935101,0.00001889827,0.00001820548,0.00004706731,0.0004119292,0.0000256085,0.00005456209,0.003367325,0.9503119,0.002648869,0.04243896,0.000163145],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9024498,0.001782812,0.08962368,0.004825286,0.0001000943,0.0002150229,0.00005950758,0.00006232088,0.0008814979],"genre_scores_gemma":[0.9452186,0.0001065073,0.04813234,0.001058633,0.001280846,0.00001017737,0.0001986879,0.00005182255,0.003942379],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04276883,"threshold_uncertainty_score":0.404908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01340878279212829,"score_gpt":0.2623471681021773,"score_spread":0.2489383853100491,"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."}}