{"id":"W3200959956","doi":"10.17632/vg93bvf48h.1","title":"Raman lidar data from Capel Dewi, May 23 - 30 2016","year":2018,"lang":"en","type":"article","venue":"Data Archiving and Networked Services (DANS)","topic":"Optical Systems and Laser Technology","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lidar; Remote sensing; Environmental science; Meteorology; Geology; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001947944,0.0003094542,0.0001519369,0.001679832,0.0008560161,0.0005655573,0.0006325364,0.0002583951,0.009158106],"category_scores_gemma":[0.0006048757,0.0001479198,0.0001147733,0.001451622,0.0001575071,0.0003340651,0.0003081159,0.000335013,0.002853622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003508119,"about_ca_system_score_gemma":0.003326659,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6745659,"about_ca_topic_score_gemma":0.8882617,"domain_scores_codex":[0.9996969,0.000004661316,0.000008356878,0.00003316111,0.0002173872,0.00003961907],"domain_scores_gemma":[0.9994867,0.00001400532,0.00003395675,0.00002970467,0.0003975205,0.00003810418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001022583,0.0004192384,0.1881233,0.0007341967,0.0001368638,0.00219287,0.001659657,0.004168872,0.04591703,0.002702645,0.6060666,0.1468561],"study_design_scores_gemma":[0.0000565443,0.00006715526,0.569923,0.000128357,0.00002515741,0.0002700829,0.0009415422,0.003083022,0.01360707,0.0002601995,0.4115808,0.00005713574],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.3624436,0.0004674944,0.001640348,0.0009822935,0.0003238671,0.0004454803,0.5219507,0.0007531663,0.1109931],"genre_scores_gemma":[0.4135915,0.0005760223,0.005056122,0.0002825255,0.00007196074,0.0002172869,0.4027186,0.0001815524,0.1773044],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6745659,"threshold_uncertainty_score":0.6547014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02055324494082059,"score_gpt":0.2387948663474044,"score_spread":0.2182416214065838,"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."}}