{"id":"W4390228125","doi":"10.1007/978-3-031-37818-8_41","title":"Cloud Base Height Correlation Between a Co-located Micro-Pulse LiDAR and a Lufft CHM15k Ceilometer","year":2023,"lang":"en","type":"book-chapter","venue":"Springer atmospheric sciences","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Ceilometer; Cloud base; Lidar; Cloud computing; Remote sensing; Base (topology); Algorithm; Meteorology; Correlation coefficient; Environmental science; Computer science; Scale (ratio); Geography; Mathematics; Cartography; Machine learning","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":[0.0003183545,0.0002283255,0.000208259,0.0008200977,0.0002887823,0.000602552,0.00059068,0.0004324649,0.002632057],"category_scores_gemma":[0.0005321131,0.0002095206,0.0001958726,0.001066862,0.0001330224,0.0005511926,0.0002995564,0.0003381225,0.0009701146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00050329,"about_ca_system_score_gemma":0.0005177875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01233345,"about_ca_topic_score_gemma":0.02450167,"domain_scores_codex":[0.9998251,0.00001282924,0.000004401953,0.00004064296,0.00008327108,0.00003375119],"domain_scores_gemma":[0.9996936,0.0001163496,0.00002683929,0.0000282083,0.0001131088,0.00002197346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001025605,0.0002777281,0.2456589,0.0002411023,0.000227441,0.0008695486,0.0003675957,0.0366566,0.2648453,0.004302187,0.02222854,0.4232993],"study_design_scores_gemma":[0.00005477945,0.000305867,0.6070129,0.00006759742,0.0001209718,0.0007790308,0.0002405806,0.2723676,0.1040903,0.001472888,0.01337695,0.0001103544],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9030355,0.001644968,0.04986935,0.000356674,0.0003444033,0.00006442996,0.004371522,0.001774069,0.03853921],"genre_scores_gemma":[0.9770675,0.0002016339,0.01408941,0.00007523783,0.00005477099,0.00001366457,0.001935255,0.0001145505,0.006447959],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01233345,"threshold_uncertainty_score":0.02452332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02122504156138936,"score_gpt":0.2358544631773659,"score_spread":0.2146294216159766,"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."}}