{"id":"W6908310052","doi":"10.26023/6afe-9y4r-y50q","title":"WSR-88D Radar Mosaic, with King City, in mdv format. Daily tar archives with CIDD/JADE directory structure.. Version 1.0","year":2014,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Directory; Radar; Data set; tar (computing); Data file; Range (aeronautics); Secondary surveillance radar","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":[0.0006297955,0.002080629,0.001433752,0.003005674,0.001189056,0.002365392,0.003225132,0.001355271,0.05849377],"category_scores_gemma":[0.003110135,0.001082542,0.0009893667,0.007425135,0.0005805522,0.001554873,0.00205164,0.001432618,0.1086443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003598346,"about_ca_system_score_gemma":0.006035096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.445294,"about_ca_topic_score_gemma":0.6135255,"domain_scores_codex":[0.9992784,0.00004593601,0.00007392399,0.0001821278,0.0002364611,0.0001831443],"domain_scores_gemma":[0.9980779,0.0001545949,0.0001557671,0.0005079835,0.0008761508,0.0002276007],"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":[0.00002978212,0.000008765805,0.000771247,0.0002314716,0.00001790967,0.00001458991,0.0000352201,0.000144035,0.0001612008,0.0001590316,0.9969502,0.001476644],"study_design_scores_gemma":[0.0001178996,0.000009487688,0.01322258,0.000201929,0.00002884059,0.00004129549,0.0002213353,0.0003537834,0.000637364,0.000654383,0.9844636,0.00004762788],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001242895,0.00002305048,0.00006524941,0.0000314293,0.0000182718,0.000009010383,0.9985698,0.0004053236,0.0007535856],"genre_scores_gemma":[0.0002971586,0.00002438761,0.0001777543,0.00001168098,0.000004336533,0.00002454771,0.9986552,0.0001102274,0.0006947172],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.445294,"threshold_uncertainty_score":0.8854041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01853446934571304,"score_gpt":0.269152016719467,"score_spread":0.250617547373754,"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."}}