{"id":"W6931084227","doi":"10.5281/zenodo.3369999","title":"vol2bird: Vertical profiling of biological scatterers from weather radar data","year":2019,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Merge (version control); Radar; Merge algorithm; Secondary surveillance radar; File format; Profiling (computer programming); Web page; Data file","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":[0.001183638,0.00132359,0.0006974766,0.001452909,0.0006034083,0.002768534,0.001704933,0.0007415105,0.1190516],"category_scores_gemma":[0.003449533,0.001032299,0.0009486249,0.001534974,0.0003236623,0.002422665,0.001783312,0.001280403,0.112856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006542584,"about_ca_system_score_gemma":0.0007116012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008438554,"about_ca_topic_score_gemma":0.009797638,"domain_scores_codex":[0.9992948,0.00005608893,0.00003762545,0.0001447757,0.000387509,0.00007916455],"domain_scores_gemma":[0.9986386,0.0002638177,0.00006869179,0.0004714785,0.0004295123,0.0001278938],"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":[0.0002485876,0.00002142799,0.001281969,0.0002278311,0.00005462839,0.00009886907,0.0001370051,0.001513876,0.003929432,0.001745954,0.9429243,0.04781608],"study_design_scores_gemma":[0.0001117428,0.00003740376,0.00380424,0.00008564059,0.0000266791,0.0001724696,0.00007166289,0.006883322,0.01301563,0.002415423,0.9732955,0.0000802424],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.005313202,0.0004320641,0.09564498,0.0005362176,0.001043961,0.0002011462,0.3473477,0.4682997,0.08118102],"genre_scores_gemma":[0.02816595,0.0003577495,0.07191257,0.0003372353,0.0002352004,0.0003143199,0.6265526,0.2130542,0.0590703],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.1190516,"threshold_uncertainty_score":0.3982671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1570502301373661,"score_gpt":0.3025890736998117,"score_spread":0.1455388435624456,"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."}}