{"id":"W2787016146","doi":"","title":"Rainfall attractors and predictability","year":2013,"lang":"en","type":"article","venue":"36th Conference on Radar Meteorology (16-20 September, 2013)","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Predictability; Attractor; Climatology; Mathematics; Environmental science; Econometrics; Computer science; Statistics; Geology","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":[0.0005288591,0.0001846143,0.0003020056,0.001006424,0.000432689,0.00217184,0.0002473953,0.0003529339,0.004496119],"category_scores_gemma":[0.005848885,0.0002135945,0.0002570557,0.0006000389,0.0009356349,0.001807471,0.001293042,0.0008887639,0.0002399562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005977964,"about_ca_system_score_gemma":0.0002466422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001438842,"about_ca_topic_score_gemma":0.0009995017,"domain_scores_codex":[0.9998782,0.00003107929,0.000008010891,0.00003562476,0.00002106093,0.00002604763],"domain_scores_gemma":[0.9986472,0.0006747025,0.0002816382,0.0001132266,0.000128044,0.0001551313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002356329,0.00005056146,0.05003366,0.00009074153,0.000149908,0.0003490428,0.0009390432,0.08683534,0.002868285,0.7681771,0.01010708,0.08016357],"study_design_scores_gemma":[0.00002800989,0.00004268572,0.03047709,0.00004281839,0.00004096047,0.0001663506,0.0004703521,0.2511666,0.0005217076,0.7103999,0.006602632,0.00004091065],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8983514,0.003932836,0.04947319,0.008256556,0.0003373288,0.00001713932,0.0006215876,0.0003832684,0.03862658],"genre_scores_gemma":[0.9969817,0.0004015491,0.0009086944,0.00003903484,0.00008610548,0.000005733222,0.00009785021,0.00001950557,0.001459891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004496119,"threshold_uncertainty_score":0.01504105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03066199986499975,"score_gpt":0.2335256468251767,"score_spread":0.2028636469601769,"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."}}