{"id":"W3008903256","doi":"10.5430/ijhe.v9n2p270","title":"Prevalent Crime in Nigerian Tertiary Institutions and Administrative","year":2020,"lang":"en","type":"article","venue":"International Journal of Higher Education","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Harassment; Stratified sampling; Tertiary institution; Institution; Sample (material); Cronbach's alpha; Socioeconomics; Population; Crime prevention; Criminology; Geography; Business; Psychology; Medical education; Demography; Social science; Sociology; Medicine; Social psychology; Service (business); Marketing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005761107,0.0001948746,0.0002395621,0.001825723,0.001694305,0.001345705,0.000357837,0.0003065369,0.002308292],"category_scores_gemma":[0.00279708,0.0002623631,0.0001718851,0.001714,0.0007913954,0.0004981428,0.00102574,0.0005386572,0.0002201676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001348141,"about_ca_system_score_gemma":0.001966754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01407367,"about_ca_topic_score_gemma":0.02611123,"domain_scores_codex":[0.9991876,0.0001726367,0.0001355753,0.00007239687,0.0001820165,0.0002498146],"domain_scores_gemma":[0.9970534,0.0002773999,0.001795958,0.00008505944,0.0003378651,0.0004502718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002144092,0.00007295492,0.9908453,0.00004664437,0.000006610136,0.000486263,0.003689156,0.00002412778,0.0001112683,0.0001915098,0.0002704546,0.004234287],"study_design_scores_gemma":[0.000001752461,0.00009038285,0.9718497,0.00009412484,0.000009161267,0.00120605,0.02529602,0.00007911787,0.0001230848,0.00007026401,0.001171704,0.000008611156],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990067,0.000123991,0.00002391587,0.00007423731,0.000003673364,0.00001060087,0.0000485049,9.226189e-7,0.0007075067],"genre_scores_gemma":[0.9993242,0.0002404741,0.00005971397,0.00004522855,0.000003403128,0.0000068955,0.00004826773,7.994561e-7,0.0002710125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01407367,"threshold_uncertainty_score":0.02798349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05570808283240825,"score_gpt":0.3661777429711328,"score_spread":0.3104696601387245,"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."}}