{"id":"W2560163360","doi":"","title":"FEARING ONLINE IDENTITY THEFT: A SEGMENTATION STUDY OF ONLINE CUSTOMERS","year":2016,"lang":"en","type":"article","venue":"European Conference on Information Systems","topic":"Digital Communication and Language","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Identity theft; Internet privacy; Computer science; Identity (music); Segmentation; Computer security; Business; Artificial intelligence; Aesthetics","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":[0.0004996817,0.0001091621,0.0001375738,0.0002048999,0.00006686438,0.0003241824,0.0009411507,0.00001569637,0.00001210502],"category_scores_gemma":[0.0000584667,0.00007532469,0.00003118943,0.0002566398,0.00002499829,0.003567351,0.000257682,0.00007110855,0.0003393792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004082395,"about_ca_system_score_gemma":0.00003435777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006205104,"about_ca_topic_score_gemma":0.00003021832,"domain_scores_codex":[0.9984996,0.0002827063,0.0005626545,0.000119533,0.0004189455,0.0001165186],"domain_scores_gemma":[0.9985487,0.00005202325,0.0004255469,0.0006865295,0.0002279545,0.00005917859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0000626696,0.001721546,0.003196908,0.0001545907,0.0001188379,0.000009865732,0.04250756,0.0006917761,0.002806815,0.5304083,0.0005055014,0.4178156],"study_design_scores_gemma":[0.02427481,0.00650703,0.516572,0.004111626,0.00008829287,0.0001108885,0.2676392,0.08043867,0.001828106,0.0003932856,0.09446882,0.003567308],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6581277,0.00001672968,0.1101074,0.0003809323,0.0003779707,0.0007933036,0.00006898758,0.0003365038,0.2297904],"genre_scores_gemma":[0.9992133,0.00001047078,0.0002640812,0.0001060748,0.00001515866,0.000005067473,0.00002621619,0.000005358948,0.0003542204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.530015,"threshold_uncertainty_score":0.4362147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0510747633396778,"score_gpt":0.2966486221212811,"score_spread":0.2455738587816033,"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."}}