{"id":"W2885487231","doi":"","title":"Toward an Attractor of Radar Precipitation Data","year":2015,"lang":"en","type":"article","venue":"37th Conference on Radar Meteorology","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Radar; Precipitation; Attractor; Meteorology; Climatology; Remote sensing; Computer science; Geology; Geography; Mathematics; Telecommunications","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":[0.003263423,0.0005150227,0.0009707618,0.002603559,0.0008765399,0.003852645,0.001068034,0.0009698901,0.004553653],"category_scores_gemma":[0.02652332,0.0007094496,0.0007750522,0.001504434,0.001428106,0.007994806,0.005856922,0.002662215,0.001020216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001385059,"about_ca_system_score_gemma":0.001175585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002491572,"about_ca_topic_score_gemma":0.001447389,"domain_scores_codex":[0.9990146,0.0003961043,0.00007585908,0.0002710508,0.0001734204,0.00006893268],"domain_scores_gemma":[0.9932012,0.002949892,0.0006259821,0.001334777,0.001367608,0.0005205302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003244856,0.00008871972,0.01097598,0.0001342511,0.0001044221,0.000173676,0.0005626205,0.07396929,0.002336189,0.7844909,0.008246977,0.1185924],"study_design_scores_gemma":[0.00003153884,0.00006287447,0.001540541,0.00009759954,0.00002718356,0.00007586293,0.0001278933,0.5639527,0.001224968,0.4200337,0.01279027,0.00003488122],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06430062,0.001121514,0.9146665,0.005619048,0.0003908996,0.00004883028,0.001221606,0.001048212,0.01158278],"genre_scores_gemma":[0.7276534,0.002010169,0.2582708,0.0007313038,0.0006015461,0.0001643085,0.00218777,0.0006273359,0.007753275],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004553653,"threshold_uncertainty_score":0.01725888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2386475109183433,"score_gpt":0.3145134679307113,"score_spread":0.07586595701236806,"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."}}