{"id":"W4205385348","doi":"10.17762/de.vol2022iss1.8685","title":"Cyberspace and Women- Dimensions of Cybercrime against Women in India","year":2022,"lang":"en","type":"article","venue":"Design Engineering","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cybercrime; Stalking; Cyberspace; Legislation; Anonymity; Internet privacy; Hacker; Government (linguistics); The Internet; Political science; Law; Criminology; Computer security; Sociology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005475304,0.0001154844,0.0001964215,0.0002175364,0.00009282426,0.00001741954,0.0002517449,0.00001746282,0.00001082591],"category_scores_gemma":[0.00003494918,0.0001132375,0.00001904177,0.0004613435,0.00001522639,0.0001535943,0.0004843817,0.0001417328,0.000001554917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002377083,"about_ca_system_score_gemma":0.00002909258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005340028,"about_ca_topic_score_gemma":0.0000011216,"domain_scores_codex":[0.9989947,0.00003845963,0.0001759063,0.0002061276,0.000183081,0.0004017111],"domain_scores_gemma":[0.9995357,0.0001245199,0.00002964726,0.0002194253,0.00001213508,0.00007860327],"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":[0.00007504549,0.0004281689,0.004590056,0.0001945131,0.0003503115,0.0002546302,0.2028418,0.5506509,0.1120187,0.1131045,0.00249589,0.01299544],"study_design_scores_gemma":[0.01097415,0.003325474,0.2525336,0.0003445852,0.00005024059,0.0001302635,0.0214918,0.5590504,0.03365419,0.004900521,0.1082966,0.005248195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9332997,0.0003624822,0.0644773,0.0000812012,0.000195585,0.0002515926,0.000003032202,0.0001291093,0.001200039],"genre_scores_gemma":[0.9950761,0.00004780412,0.004460589,0.0000912863,0.000008068328,0.0001473981,6.434162e-7,0.00001016285,0.0001579737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2479436,"threshold_uncertainty_score":0.4617692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01010699926691865,"score_gpt":0.1963656254006087,"score_spread":0.18625862613369,"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."}}