{"id":"W3000569684","doi":"10.1080/0960085x.2019.1708218","title":"Advancing a NeuroIS research agenda with four areas of societal contributions","year":2020,"lang":"en","type":"article","venue":"European Journal of Information Systems","topic":"Neural and Behavioral Psychology Studies","field":"Neuroscience","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Field (mathematics); Leverage (statistics); Engineering ethics; Information system; Societal impact of nanotechnology; Strategic information system; Management science; Publishing; Data science; Knowledge management; Sociology; Management information systems; Political science; Computer science; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001159639,0.00009139536,0.0002196002,0.0001221592,0.0001929402,0.00006888171,0.0002742652,0.00001360933,0.000006854474],"category_scores_gemma":[0.0007137792,0.00006060667,0.00008074015,0.0004514258,0.0001596676,0.0008844674,0.00006364852,0.0003835808,0.00008649856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002450958,"about_ca_system_score_gemma":0.00004805715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001903093,"about_ca_topic_score_gemma":1.665468e-7,"domain_scores_codex":[0.9977087,0.0006986875,0.0007427323,0.00008205268,0.0005623258,0.0002055046],"domain_scores_gemma":[0.9983031,0.0001318233,0.0006903206,0.00009375273,0.0006545543,0.0001264912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001859137,0.0002739521,0.01341789,0.0005760308,0.0001381934,0.001855077,0.02737,0.004463065,0.801733,0.001002132,0.135022,0.01228959],"study_design_scores_gemma":[0.01563152,0.01977227,0.05439133,0.001746491,0.0002362571,0.0116753,0.04014925,0.001618234,0.2993959,0.00004116935,0.5539936,0.001348616],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847525,0.00007502501,0.003690793,0.003465513,0.0004341017,0.0002637776,0.00004945512,0.0000298404,0.007239006],"genre_scores_gemma":[0.9991775,0.00002788063,0.00004816964,0.0005612166,0.0001331467,0.000001010615,7.591036e-7,0.000007316724,0.00004303912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.502337,"threshold_uncertainty_score":0.2471468,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2296755877491406,"score_gpt":0.3933228068422704,"score_spread":0.1636472190931298,"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."}}