{"id":"W4389891322","doi":"10.3390/app132413346","title":"Exploring and Visualizing Research Progress and Emerging Trends of Event Prediction: A Survey","year":2023,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Beijing Association for Science and Technology; China Scholarship Council; Ministry of Natural Resources of the People's Republic of China","keywords":"Data science; Field (mathematics); Citation; Event (particle physics); Computer science; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.005952544,0.001133898,0.000866954,0.04436516,0.0008450808,0.005106873,0.0009427349,0.0008303844,0.003170322],"category_scores_gemma":[0.02630405,0.0004384571,0.001036658,0.05367639,0.0007789284,0.007744393,0.001576589,0.0007482173,0.00126373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00089457,"about_ca_system_score_gemma":0.001704041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005198672,"about_ca_topic_score_gemma":0.007059629,"domain_scores_codex":[0.9965486,0.0008999481,0.0006474317,0.0006687992,0.001063138,0.0001721707],"domain_scores_gemma":[0.9600229,0.03022655,0.003333326,0.001345839,0.004465568,0.000605877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001561355,0.00007509664,0.09188982,0.02011616,0.0004235574,0.0004669061,0.00704253,0.003599436,0.002769528,0.0146559,0.04132008,0.8174848],"study_design_scores_gemma":[0.00002816417,0.0001788018,0.1243709,0.01480391,0.000828232,0.00141936,0.01503973,0.0152813,0.00585781,0.02934996,0.792589,0.0002527649],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.1629162,0.6653711,0.06890589,0.01145837,0.001292994,0.000278115,0.03889223,0.004943698,0.04594134],"genre_scores_gemma":[0.3830976,0.508469,0.06607859,0.001079832,0.001295572,0.0003329981,0.03467963,0.0007815148,0.00418521],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9556348,"threshold_uncertainty_score":0.03148037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3725692043739006,"score_gpt":0.4182089870302184,"score_spread":0.0456397826563178,"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."}}