{"id":"W4394994370","doi":"10.26599/bdma.2024.9020016","title":"Call for Papers: Special Issue on Data-Driven Spatial and Temporal Anomaly Detection","year":2024,"lang":"en","type":"paratext","venue":"Big Data Mining and Analytics","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Anomaly detection; Anomaly (physics); Computer science; Data science; Data mining; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003109721,0.001984444,0.002030424,0.002834421,0.001808648,0.01032734,0.002894906,0.005204181,0.5195192],"category_scores_gemma":[0.01208757,0.0006784701,0.001138628,0.003361606,0.0007840452,0.006783292,0.002651057,0.004011223,0.4242702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001522499,"about_ca_system_score_gemma":0.001867869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008614907,"about_ca_topic_score_gemma":0.001971787,"domain_scores_codex":[0.9976604,0.0002199428,0.0001825843,0.0004036463,0.001356705,0.0001766835],"domain_scores_gemma":[0.9856592,0.002997891,0.0005941343,0.001242389,0.006537619,0.002968861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001652145,0.00001622575,0.00003533582,0.00005450121,0.000003800404,0.00001770212,0.000002059413,0.00004509278,0.00005434701,0.0002610588,0.9876438,0.01184968],"study_design_scores_gemma":[0.00002363927,0.00002211217,0.0002731743,0.00008021504,0.000006186446,0.00003384745,0.00001313214,0.0003648004,0.0001175032,0.001359554,0.9976957,0.00001001944],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0007030743,0.00703869,0.008673997,0.07717704,0.6138892,0.0008151084,0.007513246,0.003687765,0.2805019],"genre_scores_gemma":[0.00249586,0.00554946,0.001986095,0.009331755,0.1646724,0.0003390936,0.005827788,0.002321817,0.8074757],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5195192,"threshold_uncertainty_score":0.6853476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1020988067490999,"score_gpt":0.3243632255437527,"score_spread":0.2222644187946529,"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."}}