{"id":"W3198403047","doi":"","title":"Statistical interpretation of a scaling law for the raindrop size distribution: reconciling two papers from a quarter century ago","year":2019,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Interpretation (philosophy); Quarter (Canadian coin); Scaling law; Scaling; Distribution (mathematics); Econometrics; Law; Statistics; Calculus (dental); Political science; Mathematics; History; Computer science; Mathematical analysis; Archaeology; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008677228,0.0001124432,0.0001839369,0.000013461,0.0001441038,0.00007811603,0.0001510493,0.00004599162,0.0001551504],"category_scores_gemma":[0.0006467695,0.00008216978,0.0001004927,0.00008381,0.00005470483,0.0001406633,0.000005334231,0.0001137481,0.00006251674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008932273,"about_ca_system_score_gemma":0.00003121793,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01100094,"about_ca_topic_score_gemma":0.01255765,"domain_scores_codex":[0.9987664,0.00008860491,0.000405644,0.0002308712,0.0002975938,0.0002108576],"domain_scores_gemma":[0.9960273,0.003437638,0.0002286899,0.0001405406,0.0001011108,0.00006470172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000557297,0.00006106735,0.7410263,0.0001390292,0.0004673844,0.000005251588,0.004173381,0.1575928,0.003609891,0.0003973302,0.0003411554,0.09162916],"study_design_scores_gemma":[0.001444389,0.0001514688,0.8045141,0.0003883894,0.0003110062,0.000001742167,0.004050832,0.1844719,0.0007931671,0.00144897,0.002032315,0.0003917417],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922262,0.0002593401,0.001106858,0.0002351922,0.0003507882,0.0002282375,0.0003535394,0.00002415898,0.005215678],"genre_scores_gemma":[0.9973336,0.0000110028,0.001788588,0.0001780154,0.0001003397,0.000002570497,0.0005634322,0.000003464478,0.00001895102],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09123743,"threshold_uncertainty_score":0.9955849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01436981364196003,"score_gpt":0.2333540171361014,"score_spread":0.2189842034941414,"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."}}