{"id":"W4387896777","doi":"10.4236/acs.2023.134031","title":"Evaluation of Candidate Predictors for Seasonal Precipitation Forecasting","year":2023,"lang":"en","type":"article","venue":"Atmospheric and Climate Sciences","topic":"Climate variability and models","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre","keywords":"Precipitation; Climatology; Environmental science; Principal component analysis; Mode (computer interface); North Atlantic oscillation; Scale (ratio); Index (typography); Statistics; Meteorology; Mathematics; Geography; Computer science; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.003092941,0.001175939,0.0008826913,0.002524595,0.0005958566,0.001362929,0.0006657924,0.0004497654,0.002013591],"category_scores_gemma":[0.007165596,0.0002941663,0.000899701,0.002154274,0.0002266361,0.000835632,0.0005398829,0.0006667264,0.0006027699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000334689,"about_ca_system_score_gemma":0.00175556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007039919,"about_ca_topic_score_gemma":0.005049598,"domain_scores_codex":[0.9988838,0.000565762,0.00006688508,0.0001677365,0.0001896852,0.0001261228],"domain_scores_gemma":[0.9969056,0.002022703,0.0001882676,0.0001081516,0.0006717228,0.0001036368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00154939,0.0007030603,0.250341,0.0003627543,0.0006629418,0.0002689644,0.0001729775,0.3154655,0.005336312,0.00301201,0.00514793,0.4169772],"study_design_scores_gemma":[0.00002735384,0.0001499482,0.02226536,0.00004955478,0.0001220835,0.00003037494,0.00008127754,0.9746176,0.001345449,0.000488254,0.0008033703,0.00001948328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6930368,0.002102006,0.2954789,0.0005552916,0.0002230178,0.0003247246,0.002593356,0.001898191,0.00378774],"genre_scores_gemma":[0.9517288,0.0006026927,0.04323718,0.00002584104,0.000111175,0.0001823279,0.003194874,0.00008232535,0.0008346388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007039919,"threshold_uncertainty_score":0.01635724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05736791780673425,"score_gpt":0.2978656526409163,"score_spread":0.240497734834182,"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."}}