{"id":"W2982653624","doi":"10.36227/techrxiv.14398304.v1","title":"Predicting Rainfall using Machine Learning Techniques","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Machine learning; Reliability (semiconductor); Artificial intelligence; Set (abstract data type)","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":[],"consensus_categories":[],"category_scores_codex":[0.00105924,0.0009248618,0.0006119562,0.001881812,0.0003017137,0.001204383,0.0006695875,0.0008977743,0.0012045],"category_scores_gemma":[0.003854326,0.0002652973,0.0005335314,0.001569926,0.0002114704,0.001213828,0.0004650242,0.00088182,0.0005513786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004995358,"about_ca_system_score_gemma":0.0005098294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006425121,"about_ca_topic_score_gemma":0.004599702,"domain_scores_codex":[0.999335,0.0002231622,0.00006117007,0.0001267163,0.0001943417,0.00005966424],"domain_scores_gemma":[0.9975849,0.001757441,0.0002040214,0.0001450547,0.0002732956,0.00003524655],"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":[0.0001027491,0.0001894509,0.01242764,0.00009035519,0.00008993154,0.00008126901,0.00005586496,0.8050795,0.003794364,0.0008511108,0.001315915,0.1759219],"study_design_scores_gemma":[0.000004223167,0.00002544718,0.001222747,0.000006168516,0.00000698416,0.00001060783,0.00001709025,0.9960639,0.001395698,0.000889258,0.0003508526,0.000007056669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.340945,0.001595594,0.6435577,0.000998235,0.0001653662,0.0002486841,0.001616566,0.004235957,0.006636833],"genre_scores_gemma":[0.854313,0.0007567966,0.1418846,0.00007506383,0.0001002685,0.00009341042,0.001090147,0.00004752002,0.001639267],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006425121,"threshold_uncertainty_score":0.01277542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01691491611135579,"score_gpt":0.2658512421979068,"score_spread":0.2489363260865511,"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."}}