{"id":"W1549328980","doi":"10.1029/2012jd017753","title":"Analytical estimation of droplet concentration at cloud base","year":2012,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Supersaturation; Mixing (physics); Base (topology); Cloud base; Spectral line; Mixing ratio; Cloud physics; Cloud computing; Statistical physics; Mechanics; Physics; Computational physics; Materials science; Thermodynamics; Mathematics; Mathematical analysis; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001154906,0.0001187723,0.000280644,0.000001145174,0.0001447627,0.00002406158,0.000283321,0.00007654139,0.004223306],"category_scores_gemma":[0.0005689973,0.00008836399,0.000158248,0.0004284938,0.0005626801,0.0004519728,0.0002213415,0.0003769721,0.0003486703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003448399,"about_ca_system_score_gemma":0.00005382931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000265378,"about_ca_topic_score_gemma":0.00001286796,"domain_scores_codex":[0.9970688,0.0002552742,0.0004839257,0.0001352439,0.001522935,0.0005338241],"domain_scores_gemma":[0.9985936,0.0004104259,0.0002581319,0.0002043391,0.0001034724,0.0004299965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001479588,0.003052798,0.7521225,0.00008710028,0.0001903932,0.00006617006,0.001930047,0.01700245,0.05034638,0.008667377,0.09451285,0.0705424],"study_design_scores_gemma":[0.001680538,0.002168464,0.8354882,0.0001093621,0.00009582663,0.00006064044,0.0007209515,0.1240579,0.0215831,0.003793529,0.009847573,0.0003939081],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938235,0.000130772,0.001981689,0.0003003635,0.0001358825,0.0001116669,0.000002084875,0.000005194519,0.003508844],"genre_scores_gemma":[0.9950445,0.0000366415,0.003630918,0.00003727453,0.0003935228,0.000002415376,0.000001530517,0.0000130695,0.0008401196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1070555,"threshold_uncertainty_score":0.996687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02994290958015466,"score_gpt":0.3229757807874901,"score_spread":0.2930328712073354,"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."}}