{"id":"W6929933803","doi":"10.5065/d6862dhx","title":"FP6 University of Manitoba Doppler Lidar Zenith Pointing Data. Version 2.0","year":2015,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"NetCDF; Zenith; Data set; Lidar; Doppler effect","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001129861,0.002522243,0.001393808,0.003593041,0.001151048,0.002035783,0.003723643,0.001720156,0.02977097],"category_scores_gemma":[0.004312189,0.0007271792,0.00104819,0.006850885,0.0005769586,0.001375809,0.002019472,0.002035202,0.06275462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002371215,"about_ca_system_score_gemma":0.004353014,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.10266,"about_ca_topic_score_gemma":0.1728166,"domain_scores_codex":[0.9989811,0.0001215522,0.00009298906,0.0002611624,0.000342621,0.0002006042],"domain_scores_gemma":[0.9982139,0.0002335615,0.0001586814,0.0004224557,0.0007110082,0.0002604884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00006022443,0.00002676435,0.001373051,0.0003470555,0.00003390035,0.00002821938,0.00002987732,0.0004227423,0.0001429224,0.0004841339,0.9948242,0.002226888],"study_design_scores_gemma":[0.00012422,0.00001525091,0.006933431,0.0002183425,0.00002951177,0.00005696364,0.0001328296,0.0007442512,0.0006262619,0.001200638,0.9898832,0.00003502093],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001554829,0.00003616801,0.00006332446,0.00003811759,0.0000153022,0.000006204096,0.9989567,0.0003325637,0.0003960422],"genre_scores_gemma":[0.000315222,0.00002481205,0.000185523,0.00001595983,0.00000275756,0.00002139812,0.999071,0.00004807209,0.000315178],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.89734,"threshold_uncertainty_score":0.2041249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04351833063386163,"score_gpt":0.3093805570495307,"score_spread":0.265862226415669,"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."}}