{"id":"W4220743752","doi":"10.1002/essoar.10510778.1","title":"Using near-term forecasts and uncertainty partitioning to improve predictions of low- frequency cyanobacterial events","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"Email authentication; World Wide Web; Electronic mail; Computer science; Key (lock)","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":[0.003563229,0.0006642207,0.0004465831,0.0007589426,0.0004237036,0.001139603,0.0008172254,0.0007315114,0.0007990858],"category_scores_gemma":[0.01091663,0.0006047655,0.0007515255,0.0003692903,0.0002924577,0.001702718,0.0008890069,0.000999543,0.000152249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102044,"about_ca_system_score_gemma":0.00133819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03428444,"about_ca_topic_score_gemma":0.0348281,"domain_scores_codex":[0.9991642,0.0003710378,0.00005360221,0.00020794,0.000121063,0.00008214143],"domain_scores_gemma":[0.9956483,0.002848413,0.0005405422,0.0002428868,0.000549851,0.0001699405],"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":[0.0000786513,0.0000702328,0.0294565,0.00001863819,0.00009121717,0.00002530067,0.0001026978,0.9468332,0.001111741,0.0008462329,0.0002515315,0.021114],"study_design_scores_gemma":[0.00001082922,0.00002946609,0.007887883,0.000008123496,0.00001271177,0.000005778016,0.00002320925,0.9906096,0.0003544556,0.0008922847,0.0001485888,0.00001709612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8634912,0.0001706052,0.1329214,0.0004529721,0.0000411576,0.00003888768,0.0002975138,0.0005142123,0.002072057],"genre_scores_gemma":[0.9844848,0.00004053771,0.01485963,0.00003148391,0.00001321482,0.00001260994,0.0003313881,0.00002424924,0.0002019611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03428444,"threshold_uncertainty_score":0.06816977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02913872672037104,"score_gpt":0.2683674470220717,"score_spread":0.2392287203017006,"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."}}