{"id":"W4392758660","doi":"10.5194/egusphere-egu24-13870","title":"Investigating Deep Convective Cores Combining CloudSat Observations and Model Simulations ","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Convection; Environmental science; Computer science; Meteorology; Atmospheric sciences; Climatology; Geology; Physics","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":[0.0009038527,0.001065774,0.0005952649,0.0006860946,0.000486889,0.0008741578,0.00115038,0.001078802,0.0007177913],"category_scores_gemma":[0.001363218,0.0004470094,0.001124927,0.0009338618,0.0003037248,0.0009182526,0.0004869145,0.000707039,0.0001721538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001008085,"about_ca_system_score_gemma":0.001293906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1110166,"about_ca_topic_score_gemma":0.07636205,"domain_scores_codex":[0.9998074,0.00004494389,0.00001671569,0.00005607811,0.00002950271,0.00004533334],"domain_scores_gemma":[0.999432,0.0002056275,0.00009291861,0.00008598165,0.0001088793,0.00007452455],"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":[0.0001843127,0.00041617,0.05769123,0.00009821935,0.0003545501,0.000127126,0.000112326,0.9251412,0.004674947,0.0008786882,0.001226873,0.009094432],"study_design_scores_gemma":[0.00005693035,0.00005323939,0.01164974,0.00001073269,0.00003944432,0.000009068473,0.00004929167,0.9864454,0.0009992413,0.0002007185,0.0004684461,0.00001773301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898692,0.000207675,0.004528022,0.0001773875,0.00004278702,0.00007875384,0.002913994,0.0003518556,0.001830375],"genre_scores_gemma":[0.9859204,0.0001279013,0.009020098,0.00008160675,0.00003167705,0.00005895277,0.004332168,0.00008256752,0.0003446099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1110166,"threshold_uncertainty_score":0.2207409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1259750913362995,"score_gpt":0.2865152148324104,"score_spread":0.1605401234961109,"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."}}