{"id":"W4206111896","doi":"10.5267/j.dsl.2021.11.004","title":"Assessing the forecasting model ability in measuring the prevention transmission of COVID-19 pandemic: An application of visibility analysis using Inductive logic","year":2022,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universitas Padjadjaran; Universiti Malaysia Terengganu","keywords":"Visibility; Computer science; Operations research; Transmission (telecommunications); Stakeholder; Pandemic; Econometrics; Coronavirus disease 2019 (COVID-19); Economics; Engineering; Geography; Meteorology; Telecommunications","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":[0.00614739,0.000599741,0.0004706095,0.001908333,0.0004095673,0.001903149,0.0008437471,0.0006334266,0.0007940355],"category_scores_gemma":[0.02687519,0.0002214985,0.000850554,0.001231775,0.0006835785,0.002688873,0.001104655,0.001096899,0.0001016468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00145924,"about_ca_system_score_gemma":0.00124201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005355792,"about_ca_topic_score_gemma":0.002527773,"domain_scores_codex":[0.9970278,0.00111201,0.0002642547,0.000405136,0.0009795087,0.000211338],"domain_scores_gemma":[0.978579,0.01651188,0.001600722,0.0009977677,0.002137458,0.0001731813],"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":[0.0003893171,0.0002674701,0.1133814,0.0002350567,0.0003055417,0.0003256066,0.0009271635,0.6344878,0.006396855,0.04482759,0.001340443,0.1971158],"study_design_scores_gemma":[0.000007283025,0.0001394309,0.007973338,0.00002566641,0.00004129201,0.00006089848,0.0001962618,0.9748811,0.002956253,0.01320455,0.0004836767,0.00003020207],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4187075,0.0003671384,0.5706962,0.001191041,0.00006478377,0.000109921,0.0002595252,0.0004125452,0.008191443],"genre_scores_gemma":[0.954549,0.0001236727,0.04472426,0.00005628047,0.00001701309,0.00003328389,0.0001315145,0.00001607108,0.0003488398],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00614739,"threshold_uncertainty_score":0.03251088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1968207004522297,"score_gpt":0.4296458553985255,"score_spread":0.2328251549462958,"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."}}